Marble-Fall-Icosystem-4
@#$#@#$#@
This is a model of the "Bean Machine", a simple analog model of how 
a binomial distribution approximates a Gaussian. Marbles drop from 
an opening in the top, bounce over several rows of pegs, and are collected 
in bins at the bottom. The twist in this case is that pegs can be biased to 
push marbles left or right, resulting in all sorts of distributions.
@#$#@#$#@
Shopsim-sc
@#$#@#$#@
This model is aiming to explore using approach of multi-agent simulation (MAS) to analyse 
the impact of public transportation policies on shops's market share, especially 
on shops in central area of local cities in the context of Japan. This MAS 
model called as Shopsim has been developed to analyse central area 
regeneration policies that include the public transportation policy. 
A basic scenario (BS) and a scenario of implementing combined public 
transportation policies (CTPS) are designed to illustrated how to analysing 
the impact of transportation policies using Shopsim. Household agents in 
scenarios have to make their decision on where to go shopping and choose an 
appropriate travel mode (walking, bus or car) to go there. The spatial market 
pattern and market statistics of central area shops can be generated from 
these individual shop-choice behaviours. Through comparing market situation in 
the CTPS to that in the BS, the impacts of public transportation policies 
on shop's market share can be analysed.
@#$#@#$#@
Quorum_Sensing
@#$#@#$#@
The discovery that bacteria are able to communicate with each other changed our general 
perception of many single, simple organisms inhabiting our world. Instead of language, bacteria 
use signalling molecules which are released into the environment. As well as
releasing the signalling molecules, bacteria are also able to measure the
number (concentration) of the molecules within a population. Nowadays
we use the term "Quorum Sensing" (QS) to describe the phenomenon
whereby the accumulation of signalling molecules enables a single cell
to sense the number of bacteria (cell density). In natural environments,
there are many types of bacteria with a variety of signalling molecules.
As they employ different languages they cannot necessarily talk to all
other bacteria. Presenting the model of cellular automata proposed to
describe the main mechanisms of Quorum Sensing where Vibrio & Fischeri,
and its model using the concept of Multi-Agents System.
@#$#@#$#@
Traffic_Simulation
@#$#@#$#@
Traffic simulation tool developed with a view to analysing the likely effect of congestion-reducing schemes, in particular high occupancy vehicle lanes. It allows you to design a road system, with sources, sinks, traffic lights, speed limits, and then simulate running vehicles around it. It shows a time-space diagram to visualise the motion of vehicles, and a flow-density diagram to visualise vehicle flow rates at different vehicle densities. Includes a number of test road systems, follow links under Simulation Runnable Applets.
@#$#@#$#@
Copying_and_Associating_1
@#$#@#$#@
COPYING and ASSOCIATING -1 is a beginning in exploring the extent to which the procedures of copying and associating may be in use in the brain of a creature. It illustrates how a crossword puzzle may be solved using WORDS that have been COPIED into a memory with some regard taken for their ASSOCIATION, so that answer words and clue words are likely to be reasonably close together.
@#$#@#$#@
PopGen_Fishbowl_1
@#$#@#$#@
PopGen Fishbowl 1.0 is an agent-based population genetics simulation.  The program contains the tools to conduct virtual 
experiments violating all the assumptions of Hardy-Weinberg theory (small population, selection, mutation, migration, and non-random mating).
@#$#@#$#@
Zombie_Infection_2
@#$#@#$#@
A simulation of the social ramifications of a zombie epidemic on an organized society.
@#$#@#$#@
Miller
@#$#@#$#@
This Model qualifies and extends March's  model (1991). Miller and al. (2006) add direct interpersonal learning. By allowing for interpersonal learning in organization, they recognize that face-to-face interaction can be critical to learning performance. Developed by CLOE, University of Naples.
@#$#@#$#@
March
@#$#@#$#@
The classical March model (1991), this simulation shows the mutual learning between an organization and its members, and how this affects the learning performance of the whole organization. Developed by CLOE, University of Naples.
@#$#@#$#@
Photon_transmissivity_2
@#$#@#$#@
Greenhouse gases (GHGs) already completely block some wavelengths of radiation from leaving the atmosphere. If additional GHGs cannot reduce those wavelengths' transmissivity, then how would an increase in GHG concentration exacerbate global warming? In two ways: by increasing absorption of other wavelengths and therefore decreasing overall transmissivity; and by concentrating photon absorption (and therefore heat) in the lower atmosphere.
@#$#@#$#@
Homo_Bellicus
@#$#@#$#@
War is something of humans, we're convinced of that. Only after humans were present on 
earth did war start. But is that true? What if war was there first...
@#$#@#$#@
SimHeart
@#$#@#$#@
HeartSim is a simulation of the electrical activity in the heart. It's capable of producing many of the commonly-observed arrhythmias, such as ventricular fibrillation and atrial flutter
@#$#@#$#@
NetLogoGreenHouse
@#$#@#$#@
A simple model of how sunlight, albedo, CO2 and clouds all work together to change the global earth temperature.
@#$#@#$#@
Randomly_Walking
@#$#@#$#@
simple model of randomly walking , reproducing human population,
<br>(a) with two sexes as usual (male female) 
<br>(b) implemented, through breed ; 
<br>(c) only females can reproduce, 
<br>(d) all agents eat food to live,(food is green , no food is brown),food regrows after some time 
<br>(e) all agents grow in size according to their age and after some threshold value die due to old age
<br>(f) agents die due to food starvation too
(g)females expend more energy in reproducing
@#$#@#$#@
SSCrazyPingPong
@#$#@#$#@
My first model for NetLogo 3.1.4
@#$#@#$#@
Mouse_Aorta_Initial_Model
@#$#@#$#@
No description.
@#$#@#$#@
Urbanization_MC
@#$#@#$#@
The very existence of urban formations on all inhabited continents and throughout the history of mankind since the 3rd millennium B.C. leads to suppose a tendency of some structured societies to maximize interaction by minimizing physical distance. Were this tendency unconstrained, it should eventually lead to the concentration of all of the societys population into one single point: a situation only partially realized by the distribution of urban populations at the global scale. Models of constraints preventing its realization have thus to be proposed. We have set up one such model, using agent based simulation of food production and accessibility, in order to account for the structural constraints particular to the physical space. The simulations have notably shown that, while necessarily emerging from a society investing agricultural surplus into the upholding of specialists, an upper limit to city-growth is imposed by the phenomena of spatial friction
@#$#@#$#@
Games
@#$#@#$#@
This model is inspired in multi-agent games that people can play, following simple rules to observe emergent global patterns/behaviours. They could be seen as simpler versions of Craig Reynolds's "Boids" [1], or Hiroki Sayama's "Swarm Chemistry" [2], with the advantage that you can play these with real people.
@#$#@#$#@
Homework_highschool
@#$#@#$#@
How to use this simulation:
Choose the number of students that will be eligible for school. It allows you to choose 1 to 100 
students. Choose the percentage of students that will actually attend the high school. 
When at school and more than 50% students go to school, all the students will have to study 
5 hours a day to graduate. If less than 50% of the students go to school, only 3 hours a 
day are necessary to graduate.
@#$#@#$#@
Light-Absorption
@#$#@#$#@
This model looks at the absorption of light by colored filters. In this case the filter is a chamber filled with gas molecules that absorb specific wavelengths of light. 
It demonstrates that a filter absorbs everything EXCEPT its apparent color.
@#$#@#$#@
Evolutionary_Game_Theory_Big_Bird_Replicator_Dynamic
@#$#@#$#@
A two-player, replicator dynamic model of evolutionary game theory is simulated in this program. The model contains two breeds of birds that randomly play a simultaneous game with other birds.  Each breed is "hard-wired" to play their breed's strategy.  The model allows the user to set different payoffs for each of the four possible matches between breeds, thereby simulating situations of repeated cooperation and/or competition.  These payoffs determine each type's reproductive success.  The model also allows the user to change the overall birth and death rate. The program contains a series of self-directed questions regarding replicator dynamic stability.  The self-directed questions also explain how to simulate the well-known "Hawks and Doves" game and then compare stability with a mixed Nash equilibrium.   This model is used in conjunction with the simpler "Evolutionary Game Theory: Mayberry" model to teach evolutionary game theory.
@#$#@#$#@
Evolutionary_Game_Theory_Mayberry_ESS
@#$#@#$#@
The Evolutionarily Stable Strategy (ESS) idea found in evolutionary game theory is simulated. The model uses a two-lane road and two driver types.  If a right-hand side driver meets a left-hand side driver, one driver dies. The process continues until only one driver type remains as the surviving strategy.  The program contains a series of self-directed questions regarding ESS that include exercises in how ESS relates to Nash Equilibrium.  This model is used in conjunction with the more complex "Evolutionary Game Theory: Big Bird Replicator Dynamic" model to teach evolutionary game theory.
@#$#@#$#@
SolarSystem-Timer
@#$#@#$#@
This model is a modification of "Solar System" by Jerry James (2/13/03). This version focuses on the relative orbit times of the planets. It adds an orbital counter so that one can compare the radii versus the orbiting times of the six historical planets.
@#$#@#$#@
Cluster
@#$#@#$#@
The objective of this model is to study the dynamics of learning processes within industrial clusters, in relation to the structural properties of network relations.
@#$#@#$#@
MASforSeg
@#$#@#$#@
This program presents an adaptative approach based on a multi-agents system for the images segmentation. This system is constituted at the micro level of autonomous entities, which deployed on the image. They are equipped with a capacity to estimate the homogeneity of a region from their current locality. Each entity exhibits several behaviours in response to the local stimulus. It can migrate, reproduce, or diffuse within the image. Various entities explore the image and label the pixels when they belong to homogeneous segments. The interactions at the micro level allow the emergence of a new feature that is segmentation of the image.
@#$#@#$#@
SAfri_Models
@#$#@#$#@
These models are based on the Wolf-Sheep Predation Model that tries to see what conditions will produce a stable ecosystem without extinction of humans or cows. 
@#$#@#$#@
Toy_Infection_Model
@#$#@#$#@
This is a simple model of the acute inflammatory response to infection.  This model is an extremely reduced version of the "Innate Inflammatory Response" model seen on the Community Models page from May 2004, and contains only some essential components of the body's response to infection.  The background patches of the model represent a generic tissue that contains a "tissue-life" patch variable that keeps track of the damage done. 
@#$#@#$#@
Gas_Distillation
@#$#@#$#@
Builds on previous Gas Lab models and tries to implement changes in particle size, mass and the influence of 'gravity'.  Model consists of a two part container with a hot side to heat the gas and a cool side to let it condense. 
@#$#@#$#@
Bifurcacion2
@#$#@#$#@
This model is an application of the famous Bifurcation diagram of logistic equation: X[t+1] = k * X[t] * (1 - X[t]); with k=0..4 and X[t]=0..1
@#$#@#$#@
Negotiations
@#$#@#$#@
This model simulates negotiations between 3 types of agents, each with a different "toughness" property. It shows how the toughness affects the outcome of the negotiations in different environments. It also demonstrates dynamic toughness strategies in which the toughness is determined dynamically according to the environment, attempting to yield good results in different environments.
@#$#@#$#@
Climate_change
@#$#@#$#@
This is a model of incoming and outgoing radiation from the sun. It demonstrates the effect on the average temperature of albedo, solar intensity, clouds, and CO2.
@#$#@#$#@
margherite
@#$#@#$#@
The model is a sort of Daisyworld with the presence of Turtles that eat the yellow flowers.
The goal of the model is to show the balancing effect of life on the environment.
@#$#@#$#@
Bug_Hunt_Evolution
@#$#@#$#@
This model is highly modified version of BugHunts Speeds to demonstrate evolution by natural selection and genetic drift. Bugs have several traits: color, hue, speed, size, and jitter. Meanwhile, the user, 'predator', has finite life which decreases over time if no bugs are caught, increases when bugs are caught, and decreases rapidly for a 'miss'.
@#$#@#$#@
forestfire2
@#$#@#$#@
Simulation of forest fires 
@#$#@#$#@
Epidemic_Typhoid_Fever_on_Disaster_Area
@#$#@#$#@
Epidemic Typhoid Fever on Disaster Area was 
inspired by tsunami disaster that hit asian countries. Typhoid fever is 
communicable disease caused by Salmonella typhii. It will easily spread to one and another 
especially on disaster area where hygiene and sanitation very poor.
@#$#@#$#@
Asteroid_Belt_Game
@#$#@#$#@
An old arcade game called "Asteroid Belt."
@#$#@#$#@
AntSystem
@#$#@#$#@
The Ant System algorithm can be used to find the shortest path in a graph by employing the same decentralized mechanism exploited by ant colonies foraging for food.
@#$#@#$#@
Gaslab_Brownian_Motion
@#$#@#$#@
Brownian motion simulation. See the spores execute the "drunkards walk." Normally the gas molecules are invisible, but you can make them visible to show how the drunkards walk originates.
@#$#@#$#@
Big_Bang
@#$#@#$#@
Simple Big Bang simulation. Shows how the Big Bang results in the pattern that distant stars are receding more rapidly. Reverse the recession to "run the movie backwards" and show how this recession velocity pattern supports the Big Bang.
@#$#@#$#@
Gaslab_Two_Color_Gas
@#$#@#$#@
Statistical Mechanics illustration using a gas of identical particles except that there are molecules of two different colors. Can illustrate mixing of gases, pressure on a wall, and the irreversability of water melting ice.
@#$#@#$#@
Newtonian_Relativity
@#$#@#$#@
Illustration of Newtonian Relativity. A car driving on top of a railroad flatcar illustrates the concepts of Newtonian Relativity and the simple addition of displacements and velocities.
@#$#@#$#@
SickTown
@#$#@#$#@
Studying the spread of infectious diseases in a small town environment.
@#$#@#$#@
Quantum_Financial_Market
@#$#@#$#@
This is a evolutionary quantum game theoretical model of a financial market, introduced and tested empirically by C.P. Gonalves and C. Gonalves (2007).
@#$#@#$#@
LogoMoth
@#$#@#$#@
LogoMoth models allow users to simulate an iterated prisoners dilemma game (see http://en.wikipedia.org/wiki/Prisoner's_dilemma) in which preprogrammed strategies interact with each other by either cooperating or defecting and/or staying or leaving. LogoMoth is modified from the traditional model in two important ways: First, individuals may, depending on their strategy, choose to leave their partner. Second, leaving and being left (i.e., staying) may incur a cost.
@#$#@#$#@
FractalMorph
@#$#@#$#@
Fractal morph is a NetLogo implementation of Richard Dawkins biomorphs. Users mimic evolution by selecting fractals from a fractal landscape.
@#$#@#$#@
Bouncing_Ball
@#$#@#$#@
This simulation models the internal dynamics of a bouncing ball. Ordered energy becomes more and more disordered as the ball bounces.
@#$#@#$#@
Vertical-Evacuation
@#$#@#$#@
This model demonstrates "vertical evacuation," a technique for bringing people to safety by having them "go up" in buildings, for instance, in flooding or tsunami situations. The model implements two behaviors: seeking to go up (modeling people who receive and understand the warning, know what to do and do it), and seeking to get outside (modeling people who want to get out for whatever reason). It also illustrates socially transimitted behavior in the form of "directors" who are able to convince individuals around them to change their behavior.
@#$#@#$#@
Wireless-Coop-Mobile
@#$#@#$#@
Model of cooperation a mobile ad-hoc wireless network based on WLAN (IEEE808.11) technology. Units move around randomly and establish cooperative clusters according to strategies in order to improve power consumption.
@#$#@#$#@
Example-HPP-3D
@#$#@#$#@
In this model we apply stochastic models to study two variations of the Lattice Gas 
Cellular Automata (LGCA), introduced by Hardy, De Pazzis and Pomeau, called HPP model. 
These are discrete models based on point particles that move on a lattice, according to 
suitable and simple rules in order to mimic a fully particle dynamics.
@#$#@#$#@
Simulation_of_Inelastic_Collision
@#$#@#$#@
This is a simulation that illustrates inelastic collision between two trolleys 
(in this case two model cars A and B) moving over a low-friction surface [Friction is 
too small and therefore can be neglected]. This is a classic simulation that shows 
that the total momentum is conserved i.e. total momentum before collision = total 
momentum after collision.
@#$#@#$#@
MEQU
@#$#@#$#@
MEQU (Market Effects of Quality Uncertainty) is a model designed to study 
the effects of quality uncertainty and incomplete information on market dynamics. 
The main assumption in this model is that buyers form quality expectations about products 
based on their own past experiences and on the experiences of people they know.
@#$#@#$#@
Urban-Transition
@#$#@#$#@
The model simulates the development of an urbanized area through the transition of land use 
from rural to urban. The model starts with a central city and a number of settlements 
distributed randomly around it. An attribute of the patches called ''possibility'' is used 
to determine the transition of tha land  use when a certain threshold is reached. The growth 
starts rather slowly but finally starts to expand rapidly. Two conditions are used in two 
specific times to impose a boundary in urban development and therefore to preserve some 
undeveloped land. The total space is divided in two zones according to the distance from 
the center and therefore the possibility of land-use transition near the central city 
is greater.
@#$#@#$#@
Recrystallization
@#$#@#$#@
Recrystallization comes from two words: re and crystallization. It means that 
there was a preceding crystallization process occurring in a material before the similar 
process occurs for the second times. Recrystallization happens in all kinds of material: 
metal, ceramic, polymer, as long as the material has crystal structure. This model represents 
the general appearance of recrystallization microstructure in materials.
@#$#@#$#@
MMG
@#$#@#$#@
Implementation based on Daniel B. Stouffer's MG implementation.
@#$#@#$#@
Obstruction_Model
@#$#@#$#@
This is my final model allowing for placing an obstruction or "barrior" in front of doorway causing agent organization.
@#$#@#$#@
Multi_Exit
@#$#@#$#@
This is my second modeling allowing for variation among number and size of exits
@#$#@#$#@
Final_Preliminary_Model
@#$#@#$#@
This is my first Evacuation model with one exit, one agent wide
@#$#@#$#@
Network_growth
@#$#@#$#@
This is a simulation of the growth of a social network based on the paper "Structure 
of growing social networks" (Emily M. Jin, Michelle Girvan, and M. E. J. Newman). The network 
presents social network characteristics, i.e. high clustering and low average geodesy. 
@#$#@#$#@
web4
@#$#@#$#@
Simulation of sessions and transactions on WebLogic.
@#$#@#$#@
ejb6
@#$#@#$#@
Simulation of Enterprise JavaBean (EJB) creation and execution on WebLogic 8.
@#$#@#$#@
MG_cem_changed
@#$#@#$#@
Majority-Minority game. Extended version of Minority Game Model. In this model, a variable 
percentage of the agents seek to be in the majority while the remainder of the agents seek 
to be in the minority. Read MG Model for implementation details like how scores are set and 
how agents choose strategies. Counterintuitive results: Memory=4 yields more efficient outcomes 
than Memory=12, especially when more than half the population wants to be in the majority. The 
information part will be modified, now it only contains information about the MG model.
@#$#@#$#@
Innovation
@#$#@#$#@
Diffusion of Innovations - agent-based model examining the spread of innovations 
by word-of-mouth ("internal diffusion") and mass media ("external diffusion"). Two sets 
of innovations can be examined at once, allowing a second "disruptive" innovation to 
compete with a recently introduced technology.
@#$#@#$#@
energy-conservation
@#$#@#$#@
This is a simple model that illustrates that total energy in a closed system is conserved. In this model, a ball has been allowed to fall freely (under gravity), hits the ground and bounces back. The energy variation of the ball has been simulated in this model.
@#$#@#$#@
Final Project
@#$#@#$#@
Here is a simulation that describes Newton's Second Law.
@#$#@#$#@
Learning and Creativity
@#$#@#$#@
This model is a representation of the occurence of learning and creativity for a very simple, 
hypothetical creature. The creature is motivated by an urge that has to be satisfied and it 
is helped by learning from received inputs. Making this model and reviewing the probable 
origins of a creature's neurobiology has suggested a direction in which it may have been 
extended for larger brains. 
@#$#@#$#@
CharityWorld-JASSS
@#$#@#$#@
CharityWorld-JASSS is a model designed to show the emergent effects of floating-point 
errors in agent-based models. This is done by showing how the model behaves dramatically 
differently using floating-point arithmetic and using real arithmetic. CharityWorld-JASSS 
also illustrates how floating-point problems can be avoided by using two simple techniques: 
Tolerance Windows, and Round to n significant digits. 
@#$#@#$#@
SpatRain
@#$#@#$#@
The SpatRain simulator described here is 
constructed to generate time series of rainfall that are fully compatible with existing 
station-level records of daily rainfall, but yet can represent substantially different 
degrees of spatial autocorrelation.
@#$#@#$#@
Craps
@#$#@#$#@
This is Craps, the dice game (Without the gambling, of course.)
@#$#@#$#@
Quicksort
@#$#@#$#@
No description given
@#$#@#$#@
MusiqueMulti-Agents
@#$#@#$#@
Mod&egrave;le exp&eacute;rimental multi-agents pour la cr&eacute;ation musicale. Chaque agents a un 
comportement tr&egrave;s simple. La mise en oeuvre d'une multitude d'agents et leurs 
interactions entre eux (et avec un signal entrant), donnent une &eacute;mergence de forme musicale.
@#$#@#$#@
AdoptLearnOnLine
@#$#@#$#@
This is a simple model about landscape transformation by farmers. The 
model simulates on how farmers decide to practice particular land use system 
on their plots, given that they have 3 choices available. The basic premise of 
the model is that farmers adopt certain land use system based on their knowledge 
about profitability of the system and their ability to generate capitals for establishment.
@#$#@#$#@
GarbageCan
@#$#@#$#@
The "Garbage Can" is a model of organizational decision-making. In the 
Garbage Can model, decision is made when the members of an organization 
apply a solution to an opportunity for making a choice. Note that solutions exist 
before problems, and that decisions can be made even without solving any problem. 
Eventually, a problem may be there to be solved, but this is not necessarily the case.
@#$#@#$#@
Example-HPP-mod
@#$#@#$#@
This model demonstrates circular wave propagation using a cellular 
automaton on a square grid. The behavior of the waves approximates 
the Navier-Stokes equation, a well established fluid dynamics equation discovered in 1823.
@#$#@#$#@
Fitness_Landsacape
@#$#@#$#@
Fitness Landscape is a NetLogo model that illustrates the principle of evolution 
as movement of a species through a fitness landscape over time.
@#$#@#$#@
Shock2004_Gut_Epithelial_Barrier
@#$#@#$#@
This is an abstract model of Epithelial Cell barrier function. 
It is based on an epithelial cell culture model that looks at the effect of cellular tight junction 
status on permeability of the epithelial cell sheet. 
@#$#@#$#@
DiffusionWithMembraneAsTurtle1
@#$#@#$#@
This is a simple model that looks at diffusion of molecules with and without the presence of a 
membrane with variable permeability. It also includes a very abstracted active transport pump 
that counteracts the permeability limitations of the membrane. 
@#$#@#$#@
DiffusionWithMembraneAsPatch1
@#$#@#$#@
This is a simple model that looks at diffusion of molecules with and without the 
presence of a membrane with variable permeability. It also includes a very abstracted active 
transport pump that counteracts the permeability limitations of the membrane. 
@#$#@#$#@
multiagent
@#$#@#$#@
The aim of our program is the creation of a financial market in which a single stock is traded; 
the agents (three categories) who act on such market are characterized by bounded 
rationality and differentiated into three types according to their behavior 
(Imitator, Fundamentalist and Stubborn); moreover, every agent has a tied budget, 
expressed by an endowment and a maximum debt they can reach before default. 
@#$#@#$#@
Reinforcement Learning Wargame
@#$#@#$#@
This model implements Q-learning (Watkins 1989) a one-step temporal difference algorithm in the area of reinforcement learning.
@#$#@#$#@
Reinforcement Learning Maze
@#$#@#$#@
This model implements Q-learning (Watkins 1989) a one-step temporal difference algorithm in the area of reinforcement learning, a branch of artificial intelligence and machine learning.
@#$#@#$#@
sudoku-solver
@#$#@#$#@
no description given
@#$#@#$#@
2d_parity
@#$#@#$#@
no description given
@#$#@#$#@
BirdAggression
@#$#@#$#@
no description given
@#$#@#$#@
LevelCrossing
@#$#@#$#@
Model of Level Crossing Operation.
@#$#@#$#@
Asynchronous_Backtracking_-_binary_random_problems
@#$#@#$#@
This is the implementation of the Asynchronous Backtracking for the random binary problems
@#$#@#$#@
ZombieInfection
@#$#@#$#@
This is a moderately faithful rewrite of Kevan Davis' Zombie Infection Simulation in NetLogo.
Go play with the original model if you haven't yet; a lot of this documentation is a comparison with the original.
@#$#@#$#@
THEmazegame
@#$#@#$#@
This is a maze game for one or two people.
@#$#@#$#@
Level_Crossing
@#$#@#$#@
The model shows operation of a level crossing installation. The macro-level pattern emerging from interconnections of micro-level behaviours of agents should ensure such conditions of operation that the longest and slowest road vehicle finding itself at the crossing (i.e. inside the hazardous area) just at the moment of activating warning lights (triggered by detection of an approaching train) is able to leave this area before the barriers are falling down.
@#$#@#$#@
Langtons_Ant_on_Infinite_Plane
@#$#@#$#@
no description submitted
@#$#@#$#@
Good_Morning_Turtles_II
@#$#@#$#@
"This is the following model of "Good morning turtles". Now each turtle can have its own values for close,far,and color. see "Good morning turles" Each turtle is facing a single turlte. Each turle moves toward the turtle it is facing until it reachs a distance define by its "close" value, then it changes its mind and escapes in the opposite direction until the distance is equal to its "far" value. Then back again to try to reach the targeted turtle.
@#$#@#$#@
ABTkernelgraphcoloring-new_interface
@#$#@#$#@
"This is the implementation of the ABT kernel for the graph coloring problem."
@#$#@#$#@
Buttons
@#$#@#$#@
"This is a NetLogo model of the buttons phase transition presented in Stuart Kauffman's book <i>At Home in the Universe</i>."
@#$#@#$#@
drawing-tool
@#$#@#$#@
"A drawing tool for NetLogo, implemented in NetLogo. 
It can be used to design initial patch color arrangements. 
It includes the usual tools--brush, line, circle-- and a multi-level undo / redo feature."
@#$#@#$#@
EasyMoney
@#$#@#$#@
"This model was made to illustrate the apparent ease with which a book' 
might be made to provide a guaranteed take, that is, if the Bookmaker 
follows these simple rules.. "
@#$#@#$#@
PileOfSand
@#$#@#$#@
" This is a simulation of a model inspired in Per Bak's pile of sand... "
@#$#@#$#@
Nonogram
@#$#@#$#@
"This program solves nonograms (sometimes) using simulated annealing. A 
nonogram is a logic problem, invented in Japan and popularised in the 
UK. It consists of a rectangular grid with one set of clues for each row 
and column of the grid... "
@#$#@#$#@
Entropy
@#$#@#$#@
"This is a model of cooling, intended to illustrate the laws of 
thermodynamics. In this simple universe, an iron block (grey) sits in a 
cloud of gas (black)... "
@#$#@#$#@
DeterminableComplexity
@#$#@#$#@
"With this model it is possible to generate some thousands of patterns 
that, incidentally, bear a reasonable likeness to printed circuit 
boards. However the model is intended to illustrate that a complex and 
apparently random pattern may not be an indeterminable collection of 
marks, and may be made by a procedure that is repeatable." 
@#$#@#$#@
SugarScape
@#$#@#$#@
"This is a version of SugarScape, as presented in 'Growing Artificial 
Societies' by Epstein and Axtell. It is preliminary, having only the 
rules: G M R S K." 
@#$#@#$#@
Logistic
@#$#@#$#@
"This is a model of a 2-D cellular automaton where each cell's state can 
take a real value between 0 and 1 and the state-updating rule consists 
of a coupled chaotic map (in this case the logistic map). Each cell 
'reads' its own state and the state of each of its four neighbours and 
updates its state accordingly. The result is an ever-changing aperiodic 
spatio-temporal pattern with large clusters of cells with states near 
each other; moreover, the global pattern emerges from a random initial 
condition, showing a more organized structure..." 
@#$#@#$#@
MagnetFun
@#$#@#$#@
"This model mimics the behavior of a magnet suspended over other magnets 
fixed on a surface such that the suspended magnet is attracted by the 
fixed ones, but cannot contact them. The resulting motion of the 
suspended magnet is random..." 
@#$#@#$#@
SolarSystem
@#$#@#$#@
"This model mimics the solar system. Setup creates the sun, five 
planets, and a 'comet'. Unlike in the real solar system, these orbiting 
bodies are in the same plane, and setup distributes the planets 
randomly. However, the planets are at the correct relative distances 
from the sun and have correct relative masses..." 
@#$#@#$#@
Imagination
@#$#@#$#@
"Imagination is the second model of a series that began with 
Self-Awareness. Imagination can surprise human beings with ideas or 
creations both unexpected and apparently from nowhere. This model 
illustrates the process of imagination by relating, with some animation, 
the events experienced by the author in making the procedure for a model 
to show trees in NetLogo..."
@#$#@#$#@
Gliders
@#$#@#$#@
"Demonstrates that gliders with arbitrary speed and direction can be 
supported with a simple cellular automata program..." 
@#$#@#$#@
Hillwalker
@#$#@#$#@
"HILLWALKER is a model inspired by the Tutorial Model 3 and it uses 
the random terrain creating code of that model, but modified..." 
@#$#@#$#@
Pathfinder
@#$#@#$#@
This is an updated version of the model I submitted in December 2002. This simulation shows how close-to-optimal paths can be found 
around obstacles with a decentralized system. In traditional 
Artificial Intelligence, the search for a good solution is typically 
viewed as a process of adding steps to a solution and backtracking 
when dead-ends are found. The alternative method pursued here is to 
have simple agents locally influence each others position. They 
globally form a path even though no agent by itself represents an 
entire solution... 
@#$#@#$#@
Ant Space
@#$#@#$#@
"Analysis of the behavioral algorithms by which army ants optimize 
their foraging behavior can provide insight into how properties of 
self-organization may influence the evolution of optimal foraging 
strategies in E. burchelli army ants..." 
@#$#@#$#@
PeerNet
@#$#@#$#@
"The model creates a peer network who's network nodes/peers come 
alive (i.e. boot and join the network) for a fixed time, then turn 
off again, dropping out of the network..." 
@#$#@#$#@
Graze # 1
@#$#@#$#@
"This is a simple pasture management or grazing model..." 
@#$#@#$#@
The Dowry Puzzle
@#$#@#$#@
"This is a well-known puzzle from statistics (e.g., Mosteller 1965). A sultan wishes to test the intelligence of his advisor, who is seeking a wife. The sultan provides a choice of 100 women, each with a different dowry. The advisor has to choose the woman with the largest dowry. He is introduced to one woman at a time, who will tell him how much dowry she will be provided with, and he can either accept them or reject her. However, once he rejects a woman there is no going back, and he has to move on to the next candidate. Which strategy is most likely to provide him with the highest dowry?"
@#$#@#$#@
Spirals & Curve Matching
@#$#@#$#@
"Alternative procedures for displaying spirals are examined and a procedure for matching equations 
to curves is developed, which may have other applications. 
Anyone of three well known spirals can be displayed by selection at the CHOICE widget. 
The Archimedes spiral is generated by a rotation plus a constant velocity crossways displacement 
as in the case of a gramophone record, giving an equidistance spacing between the lines. 
Both the evolute and the logarithmic spirals are growth spirals in which the spacing between the 
lines increases. "
@#$#@#$#@
Neteffect
@#$#@#$#@
"This project models the demand curve of consumers for a good with externalities, such as a fax machine or phone. The willingnes to buy 
this good increases when the number of bought goods increases due to more utlity of the good. Each turtle has an initial willingness 
randomly generated between 0 and 100, the willingness is a measure of money that a consumer wants to spend on the good. 
The simulation shows how different demand curve can arise when you change something. "
@#$#@#$#@
Sitsim
@#$#@#$#@
"This program models one theory of how people's attitudes are influenced by other people.  In the early 1980s, Bibb Latan? proposed a theory of 'social impact'.  The theory states that "the impact of other people on a given individual is a multiplicative function of the 'strength' of members of the group (how credible or persuasive they are), their immediacy (a decreasing function of their social distance from the individual) and their number." (Latan? 1996:65). "
@#$#@#$#@
Canal
@#$#@#$#@
"This model illustrates the well known conundrum about the operation of the Panama Canal. "
@#$#@#$#@
OilEdit
@#$#@#$#@
"Bioremediation of Oil Spills using hydrocarbon degrading bacteria."
@#$#@#$#@
OptimismAISB2
@#$#@#$#@
"This project is inspired by the phenomenon of 'motivational bias'.  It shows how the principle of maximum expected utility (MEU), can - in certain types of environment - be outperformed by 'biased' decision rules. "
@#$#@#$#@
TailModel
@#$#@#$#@
"This simulates various sinuous following behavior that one may observe with chains, pieces of rubber, and springs."
@#$#@#$#@
GameTheory
@#$#@#$#@
"This is a model based on evolutionary game theory. This theory was first applied to evolutionary processes by John Maynard Smith. Game theory is based on sub-groups of interacting agents, drawn from a meta-population, with certain payoffs occurring between the agents. These payoffs depend on the behavioral strategies of each of the interacting agents. "
@#$#@#$#@
Self-awareness
@#$#@#$#@
"Creatures have a brain that provides automatic responses for several important requirements of its body, including body regulation, mobility plus survival actions and the initial processing of sensor inputs."
@#$#@#$#@
Parity
@#$#@#$#@
"This program is an example of a two-dimensional cellular automaton. A cellular automaton is a computational machine that performs actions based on certain rules.  It can be thought of as a board which is divided into cells (such as square cells of a checkerboard).  Each cell can be either on or off. This is called the 'state' of the cell.  According to specified rules, each cell will be on (black) or off (white) at the next time step. "
@#$#@#$#@
Walk
@#$#@#$#@
"This models a simple one dimensional random walk, showing that the 
average absolute distance from the initial position converges to a 
square root function. "
@#$#@#$#@
Popeq
@#$#@#$#@
"Model 'Popeq' presents the well known population equation of biology Pn+1=APn(1-Pn) 
in a form both attractive and instructive, where the multiple iteration solutions are 
displayed in full rather than plotting only the final values. "
@#$#@#$#@
Tumor2
@#$#@#$#@
"This model illustrates the growth of a tumor and how it resists chemical treatment.  A tumor consists of two kinds of cells: parent cells (blue turtles) and transitory cells (all other turtles)."
@#$#@#$#@
AntsOpt
@#$#@#$#@
"In this model ants try to find a short path from the 
left upper corner to the right lower corner of the area."
@#$#@#$#@
Queuing Systems
@#$#@#$#@
"This page contains a small collection of models of familiar queuing systems - supermarket checkouts, an elevator, passengers boarding an aircraft. The models, and the collection are still being developed."
@#$#@#$#@
Contours & Sections
@#$#@#$#@
"This model uses the terrain modelling of Netlogo Tutorial 3, (modified), to set up a terrain and then provides for contouring and sectioning."
@#$#@#$#@
sopgm
@#$#@#$#@
"This a simple 2-D cellular automaton which represents decentralized self-organization. This is simplified version of Vote model. However behind simplicity this is able to produce complex pattern. During runing the model the red patches concentrated into a labirynth which will appear on the screen."
@#$#@#$#@
HopfieldLearning
@#$#@#$#@
"Here is a neural network (Binary Hopfield) that can identify pictures that you teach it."
@#$#@#$#@
BinaryGA
@#$#@#$#@
"This is a more elementary genetic algorithm than the ARS, which has some fun properties."
@#$#@#$#@
ARS-Genetics
@#$#@#$#@
"This is a genetic algorithm that evolves individual foragers capable of finding patches of red pixels."
@#$#@#$#@
clusterdetect
@#$#@#$#@
"This is a model that can detect different clusters of patches. This is also applicable to clusters of agents. If your agents stamp the value on which you wish to indentify clusters the algoritm can detect the clusters of the patches and the agents on them."
@#$#@#$#@
sipd
@#$#@#$#@
"Here is the Spatialy Iterated Prisoner's Dilemma with different strategies (TFT, PAVLOV, GRIM, ALLD)"
@#$#@#$#@
Flocking color
@#$#@#$#@
"A "enhanced" version of the standard flocking example - the basic simulation is unchanged, graphics and diagnostics are added: 
1. Better graphics by basing agent color by direction 
2. A clustering algorithm is included that finds the turtles in a larger group given individual neighbor sets. 
3. Two historgrams are included of the turtle directions and number of mates 
Text is provided to study self-organization and emergent properties."
@#$#@#$#@
new_wealth_distribution
@#$#@#$#@
"Expanded version of the Wealth Distribution model in the Sample Models Library.  The main changes include the possibility of patches becoming more productive, wealthy turtles now may settle on a patch and hire employees, population may no longer be constant, and turtles can now inherit wealth from their parent."
@#$#@#$#@
josephson-cooperative
@#$#@#$#@
"This is a model that solves a typical numerical problem, namely a non-linear differential equation. The interacting agents are simply the solutions of the equation at previous time steps. The equation considered here describes the behavior of a superconducting Josephson junction, however it should be simple to adapt the program to different differential equations."
@#$#@#$#@
radar
@#$#@#$#@
No Description
@#$#@#$#@
Small World Tester
@#$#@#$#@
"This links to a model for simulating political policy making in a small world network, and testing other small world measures (Watts and Strogatz, Latora).  A paper associated with the model is also on the site somewhere."
@#$#@#$#@
Predator-mediated coexistence
@#$#@#$#@
"The model illustrates the fact that predators (or, more generally, any disturbance) may  extend the length of coexistence of species competing for the same resource."
@#$#@#$#@
Building and Sorting
@#$#@#$#@
 "Social insects show all a fascinating building behavior. One of the
 most impressive kinds of collective nest construction is the building
 behavior performed by termites. This can be modeled using simple
 pick-up and drop rules.  Very similar to this building is the
 brood-sorting behavior of ants. They can discriminate between
 different brood stages and sort them in spatially distinct areas. The
 results of this sorting can be influenced from outside by
 environmental templates."  (series of 4 models)
@#$#@#$#@
Growth of Plants
@#$#@#$#@
  "Two simulations, both dealing with principal geometric rules leading
  to plant-like structures.  One leads to things like parsley or trees,
  the other one creates things looking like ferns."
@#$#@#$#@
Slime Mold Behavior
@#$#@#$#@
  "Normally [slime mold cells] move around as individual amoebas
  throughout their substrate, performing a simple random walk. But when
  the environmental situation worsens, they suddenly change their
  behavior and aggregate to a single multi-cellular body. During this
  aggregation process, a chemical signal is emmited by cells to guide
  the collective movements.  We here present 3 models that model the
  aggregational behavior of slime molds, from avery basic aproach that
  was first developed by M. Resnick up to quite elaborate versions, as
  they have been suggested by S. Camazine."
@#$#@#$#@
Daisyworld
@#$#@#$#@
"Solar luminosity is increased in a linear manner, slowly heating up
  the almost empty planet. At a certain point, the biosphere of
  Daisyworld comes up and starts to regulate the global temperature,
  still with steady increasing solar luminosity. At a certain point,
  solar luminosity gets to strong and the biosphere breaks down. After
  some time the scenario begins to lower the solar luminosity slowly and
  therefore cools down the hot and empty planet. Just watch when life
  comes back.  This is a perfect hysteresis-example you can gain from
  Daisyworld and the population and temperature plots fit almost exactly
  those published by J. Lovelock."
@#$#@#$#@
Herding
@#$#@#$#@
"This is a model of herding behaviour in a financial market. The market goes from disorganized states with great diversity of opinions to organized behaviour where there are clusters of opinions regarding the buying or selling of a financial asset."
@#$#@#$#@
connect4
@#$#@#$#@
"This is a Netlogo version of the classic Hasbro checkers game "Connect Four," in which the objective is to get four like-colored checkers in a row, column, or on a diagonal."
@#$#@#$#@
Artificial Financial Market
@#$#@#$#@
"This is a model of an artificial financial market with heterogeneous boundedly rational agents that are influenced by the sentiment of their most close colleagues regarding the future evolution of the market."
@#$#@#$#@
recursive-trees
@#$#@#$#@
"This is the "Recursive Trees" model from Resnick's "Turtles" book (pp. 110-116)."
@#$#@#$#@
turtle-ecology
@#$#@#$#@
"This is an adaptation of the "Turtle Ecology" model from the Resnick "Turtles" book."
@#$#@#$#@
layout
@#$#@#$#@
"This is a dynamic graph layout model using springs and repulsion forces to create a pleasing layout."
@#$#@#$#@
Court of the honeybee queen
@#$#@#$#@
"This simulation demonstrates a model that is assumed to explain the emergence of the queen's court in a honeybee colony. Several worker bees move towards the queen, surround her heading directly towards the queen. After some time, the bees lose again contact to the queen and move around, obviously without being influenced by her. After some time, they are again attracted by the queen and approach her directly.  The overall size of the court is stable within a certain range."
@#$#@#$#@
Lissajous
@#$#@#$#@
A simple model to draw Lissajous-figures.
@#$#@#$#@
DiscreteLife
@#$#@#$#@
NetLogo encourages the development of entity-based or agent-based models. Many 
of the systems for which NetLogo models are popular have also been modeled with 
alternative methods, such as systems of differential equations. The differences 
between these broad classes of techniques are non-trivial and of great 
importance to practicing modelers (Parunak et al. 1998). This model illustrates 
one such difference, identified by Shnerb et al. 2000. They present a simple 
scenario consisting of two interacting populations.
@#$#@#$#@
Polygons
@#$#@#$#@
This is a very simple model that shows how to draw polygons using lists and sliders.
@#$#@#$#@
connect4 and CONNIE
@#$#@#$#@
This model was extended and changed as a compliment to Michael for his original work
in giving us connect4, which is on this Netlogo Community Models site.
 A single player mode has been added by the addition of CONNIE who plays a fair game
for those who like to play against a machine.
The Procedures section includes detailed explanations of the code and some of its working can be viewed in the Command Center. 
@#$#@#$#@
Virus2
@#$#@#$#@
This is a modified version of the original Virus model. Recovered and immune individuals are able to transmit the virus. In addition sliders and monitors have been added.
@#$#@#$#@
WolfMoose
@#$#@#$#@
demonstrates how wolves are able to coordinate their activities in surrounding large prey, such as
moose, following Korf's algorithm.
@#$#@#$#@
cracks-2004
@#$#@#$#@
This model simulates the effect of randomly punching holes in a sheet of material to experimentally determine how many hole-punches can occur before the material fails. For this simulation "failure" is defined as the emergence of a continuous flaw between opposite edges.
@#$#@#$#@
drawing-tool-2004
@#$#@#$#@
A drawing tool for NetLogo, implemented in NetLogo 2.0.
The usual tools are here: brush, line, circle, box, fill, plus a multi-level undo / redo feature.
@#$#@#$#@
maze-maker-2004
@#$#@#$#@
This model builds single-path or multi-path mazes with no cross-overs.
@#$#@#$#@
watershed
@#$#@#$#@
A terrain generator demo and watershed simulator, with a nifty 3-d terrain visualizer thrown in as a bonus.
@#$#@#$#@
Genetics and Cellular Automata
@#$#@#$#@
This page holds a collection of genetics models and a few cellular automata models.  Topics include: genetic drift, Hardy-Weinberg dynamics with imperfect mixing, Hardy-Weinberg dynamics with perfect mixing, evolutionary stability of pseudoaltruism, population genetics of complete dominance, population genetics of incomplete dominance, sandpile, percolation.
@#$#@#$#@
ThermicRXN
@#$#@#$#@
This model demonstrates the connection between chemical reactions and the free energy or heat of the system.
@#$#@#$#@
bloodcells
@#$#@#$#@
This is a simulation of the control mechanism for the production 
of white blood cells based on Mackey-Glass (1977).
@#$#@#$#@
StackMachine
@#$#@#$#@
Stack Machine Simulator.  This is a model of a stack machine, also known as a zero-address computer.  The simulator may be used to verify handwritten programs and to demonstrate the action of a stack machine using randomly generated programs.  The model also demonstrates conversion from postfix (Reverse Polish Notation) expression to the normal infix notation.
@#$#@#$#@
beergame
@#$#@#$#@
An agent based model of John Sterman's Beer Game. The beer game studies irrational decision behavior induced by delays in supply chain management. It uses a board game and cards to simulate the supply chain flow.
@#$#@#$#@
5 Short-term-memory-voters
@#$#@#$#@
This short-term memory voter simulation builds on an idea presented by Howard Gardner. Imagine each voter out of a population changes her or his political opinion every day - just after visiting one of his four direct neighbors, she or he adopts the neighbors political opinion. Guess what kind of sytemic behavior will emerge over time.
@#$#@#$#@
Binary Counter
@#$#@#$#@
BinaryCounter demonstrates counting in binary, and gives the decimal equivalent of the bit pattern for various data representations. This demonstration will help you understand integer overflow and the problems it can cause when undetected. It can also ask you questions, to see how well you understand the concepts.
@#$#@#$#@
Innate Immune Response
@#$#@#$#@
This is a model of the Innate Immune Response, which is the body's initial response to injury/infection.  It is a cellular level model that focuses on the interactions between blood-borne inflammatory cells and the endothelial cells that line capillaries.  It is a ported version of a StarlogoT model that was the source for a paper that is currently under review by the Journal of Critical Care Medicine.  The model is intended to qualitatively reproduce the body's response to injury/infection, with particular emphasis on what happens to patients in the Intensive Care Unit.
@#$#@#$#@
ElFarolBarProblem
@#$#@#$#@
El Farol is a bar in Santa Fe, New Mexico, at which a band plays Irish music on Thursday evenings. The bar is enjoyable only if it is not too crowded (say more than 60% of the agents). Trying to decide whether or not to go to El Farol is what Arthur's, 1994, "El Farol bar problem" is about.
@#$#@#$#@
ProteinSynthesis
@#$#@#$#@
Protein synthesis simulation.
@#$#@#$#@
DrugPropagation
@#$#@#$#@
The primary goal of the Drug Simulation is to model the propagation of drug addiction through an infected population.  The secondary goal of this model is to determine whether making drugs illegal or legal is more effective in preventing the spread of drug addiction.
@#$#@#$#@
tictactoe
@#$#@#$#@
This is the familiar Tic Tac Toe game programmed in NetLogo where you can play against the computer.
@#$#@#$#@
accurate_clock
@#$#@#$#@
This is a simple netlogo model to simulate a clock. It has no moving part and no moving turtles (just rotating turtles and turtles that change size).
The clock can be set to any time and once set is as accurate at your computer clock.
@#$#@#$#@
HIVSIM
@#$#@#$#@
HIVSIM is an agent-based simulation of HIV immunodynamics that is currently being developped in NetLogo. It allows users to investigate dependencies between various components of the cellular and humoral immune responses to HIV. Users can interactively manipulate simulation parameters (e.g., the number of Th, Tc, and B cells, and the infectivity of viral particles) and, in real-time, observe graphical plots of the results. Additionally, users can simulate antibody and anti-retroviral therapies at various stages of infection (e.g., the user can introduce into the simulation antibodies with affinity for the dominant HIV epitope). HIVSIM is still a work in progress. As time permits, the underlying model will be further calibrated against experimental data to make it robust and applicable to the qualitative evaluation of hypotheses on HIV immunodynamics.
@#$#@#$#@
AntLines
@#$#@#$#@
This project models the behavior of ants following a leader towards a food source. The leader ant moves towards the food along a random path; after a small delay, the second ant in the line follows the leader by heading directly towards where the leader is located. Each subsequent ant follows the ant ahead of it in the same manner.
@#$#@#$#@
hypercycle
@#$#@#$#@
This model simulates a hypercycle described by Eigen and Schuster 1979. A hypercycle is a prebiotic model which shows how stable structures (e.g. life forms) can or will emerge because of cyclic support of self replicating molecules to other self replicating molecules. This model can simulate up to 10 different molecule types.
@#$#@#$#@
Drugtalk
@#$#@#$#@
Drugtalk models how rates of use of an illicit drug result from user experiences and diffusion of those experiences through social and spatial networks.
@#$#@#$#@
Bignum_Routines
@#$#@#$#@
Reporters for doing arbitrary-precision and bignum math for integer and floating-point numbers. Reporters are listed and described in the info window of the model.
@#$#@#$#@
cruise
@#$#@#$#@
This is a proof of concept for including GIS into NetLogo for a dynamic Car Cruising model within the Santa Fe downtown area. 
@#$#@#$#@
AWCS-new interface-graph-coloring
@#$#@#$#@
This is the implementation of the Asynchronous Weak-Commitment Search for the graph coloring problem.
@#$#@#$#@
DisDBnqueens
@#$#@#$#@
This model solves the N-Queens problem using the Distributed Dynamic Backtracking algorithm from  Christian Bessiere, Arnold Maestre, Pedro Meseguer.
@#$#@#$#@
DisDBgraphcoloring
@#$#@#$#@
This solves the graph coloring problem using the Distributed Dynamic Backtracking algorithm from  Christian Bessiere, Arnold Maestre, Pedro Meseguer.
@#$#@#$#@
ABTkernel
@#$#@#$#@
We solve the N-Queens problem using the ABT kernel as outlined in
"Christian Bessiere, Arnold Maestre, Pedro Meseguer.The ABT family.
In  Proceedings of  JFNP, 2002."
@#$#@#$#@
ball-fall-2004
@#$#@#$#@
This is a simple simulation of falling particles.
@#$#@#$#@
chain-of-fools-2004
@#$#@#$#@
A chain of linked turtles. They follow each other. That is, each link as a "leader". Each link steps toward its leader, until it is some minimum distance, if the leader is too close, the link steps away at a preset angle.
@#$#@#$#@
Asynchronous Backtracking-graphcoloring
@#$#@#$#@
This is the implementation of the Asynchronous Backtracking for the graph coloring problem. We solve the graph coloring problem using the ABT algorithm from "Makoto Yokoo and Katsutoshi Hirayama. Algorithms for Distributed Constraint Satisfaction: A Review.Autonomous Agents and Multi-Agent Systems, 3(2):185--207, 2000"
@#$#@#$#@
AWCS with the resolved-based learning for the graph-coloring problem
@#$#@#$#@
This is the implementation of the Asynchronous Weak-Commitment Search with the resolved-based learning  for the graph coloring problem.
@#$#@#$#@
AWCS with nogood processor centralized for the graph-coloring problem
@#$#@#$#@
This is the implementation of the Asynchronous Weak-Commitment Search with nogood processor for the graph coloring problem.
@#$#@#$#@
Unknown Gene Expression
@#$#@#$#@
This is a model that offers a series of "unknown" problems for students to explore
in learning about gene expression systems.
@#$#@#$#@
Logical Promoter
@#$#@#$#@
This is a model that demonstrates how a gene expression system can implement the full set of logical operators (AND, OR, NAND, NOR, and XOR). The expression of two genes influences the expression of the third gene, either turning it off or on, based on which logical operator has been selected.
@#$#@#$#@
lac operon
@#$#@#$#@
This is a model of the regulation of gene expression based on the lac operon: a bacterial gene that produces an enzyme that breaks down lactose, a complex sugar, into simpler sugars: glucose and galactose. This gene is only transcribed when lactose is in the environment. This system was one of the first models of gene expression described.
@#$#@#$#@
organizer2
@#$#@#$#@
Demonstration of A. K. Dewdney's idea, presented in Scientific American,  that explores how people organize their space in a digital party.
@#$#@#$#@
NukeSnake
@#$#@#$#@
This two-player arcade game is a cross between "snake" and "tank" games, and is named after the popular Macintosh shareware game by David Riggle that inspired it. It requires NetLogo version 2.1 or higher since it uses keyboard input for the controls.
@#$#@#$#@
economicexchange
@#$#@#$#@
the model tries to simulate banking and economic exchange in a small community
@#$#@#$#@
Simulation de la recherche de nourriture par les fourmis (Ant Food Search Simulation)
@#$#@#$#@
An applet, in French, showing how the ants looking for food "choose" the shortest path, if the parameters are correctly set
@#$#@#$#@
Recherche du plus court chemin entre plusieurs villes (Traveling Salesman Problem)
@#$#@#$#@
An applet, in French, showing the resolution of the Travelling Salesman Problem based on the algorithm developped by Marco Dorigo
@#$#@#$#@
Formation du cercle (Circle Formation)
@#$#@#$#@
An applet, in French, showing how a set of points "automatically" form a circle, if the parameters are correctly set
@#$#@#$#@
LNmodel127-articleVersion
@#$#@#$#@
Simulation of drop-out and student retention in a simulated learning network (paper will be published in the JASSS journal (http://jasss.soc.surrey.ac.uk/JASSS.html). 
@#$#@#$#@
ABT kernel -graphcoloring-derived in Distributed Dynamic Backtracking
@#$#@#$#@
This is the implementation of the ABT kernel - derived in Distributed Dynamic Backtracking, for the graph coloring problem.
@#$#@#$#@
ABT kernel-graphcoloring-derived in Asynchronous Backtracking-Yokoo-with temporary links
@#$#@#$#@
This is the implementation of the ABT kernel - derived in Asynchronous Backtracking (Yokoo) with temporary links, for the graph coloring problem.
@#$#@#$#@
ABT kernel-graphcoloring
@#$#@#$#@
This is the implementation of the ABT kernel for the graph coloring problem.
@#$#@#$#@
sheep-fussyfemales
@#$#@#$#@
This is the sixth and last of a series of models about adaptation and evolution for middle school. They all use a flock of sheep whose survival depends on eating grass. Fussyfemales.nlogo shows the spread of a mutation when conflicting selection pressures are present.
@#$#@#$#@
sheep-mutation
@#$#@#$#@
This is the fifth of a series of models about adaptation and evolution for middle school. They all use a flock of sheep whose survival depends on eating grass. Mutation.nlogo shows the spread of an introduced mutation, with and without selection pressure.
@#$#@#$#@
sheep-selection
@#$#@#$#@
This is the fourth of a series of models about adaptation and evolution for middle school. They all use a flock of sheep whose survival depends on eating grass. Selection.nlogo focuses on genetic drift in a variable trait of better or worse teeth, using Mendelian genetics.
@#$#@#$#@
sheep-populationC
@#$#@#$#@
This is the third of a series of models about adaptation and evolution for middle school. They all use a flock of sheep whose survival depends on eating grass. PopulationC focuses on the issue of extinction.
@#$#@#$#@
sheep-populationB
@#$#@#$#@
This is the second of a series of models about adaptation and evolution for middle school. They all use a flock of sheep whose survival depends on eating grass. PopulationB focuses on uncontrolled growth.
@#$#@#$#@
sheep-populationA
@#$#@#$#@
This is the first of a series of models about adaptation and evolution for middle school. They all use a flock of sheep whose survival depends on eating grass. PopulationA focuses on the effect of initial number, grass regrowth rate, and birthrate.
@#$#@#$#@
SOTL
@#$#@#$#@
This simulation was exended from the model "Gridlock" by Uri Wilensky & Walter Stroup, which comes with NetLogo 2.0.0 (see more info at the bottom)
Traffic lights try to "self-organize" for improving traffic.
@#$#@#$#@
ABT kernel-graphcoloring-derived in Asynchronous Backtracking
@#$#@#$#@
This is the implementation of the ABT kernel - derived in Asynchronous Backtracking, for the graph coloring problem. We solve the graph coloring problem using the ABT kernel algorithm (derived in Asynchronous Backtracking )
@#$#@#$#@
Asynchronous Backtracking-graphcoloring with flags
@#$#@#$#@
This is the implementation of the Asynchronous Backtracking with Flags for the graph coloring problem. We solve the graph coloring problem using the ABT with flags algorithm from 
Gwen-Hua C., Wei-Li Lin, Chan-Lon Wang.Asynchronous Backtracking Algorithm with no effect of nogood explosion. In Proceedings International Conference on Computer, Communication and Control Technologies - CCCT2003, Orlando, Florida. 
@#$#@#$#@
Chemical Equilibrium elaborated
@#$#@#$#@
This is a further development of the chemical equilibrium model from the Sample Models library.  Temperature, activation energy, and collision orientation are included in the model.  It is easy to change the amount of one of the chemicals, or the temperature, and observe the response of the system.  
@#$#@#$#@
Shapefactory Model
@#$#@#$#@
This is an agent based simulation of a lab experiment, Shape Factory. Shape Factory is a game for studying the collaboration patterns among distributed teams. In this game there are ten 'players', each with a different color, and each capable of producing one of five specialty shapes.  The shapes represent work that agents can do for each other, and the five different shapes represents different 'skills'. In the default versions of the game (as run with human subjects) there are ten players and five shapes, so each shape is produced by two players.Players request shapes from each other to fulfill the shape orders they receive at the beginning of a round. Each tries to collect as many shapes as they can to fulfill its orders. 
@#$#@#$#@
Emotion & Motivation
@#$#@#$#@
Following upon two Netlogo models SELF-AWARENESS and IMAGINATION this model shows that a typical human relationship between EMOTION &amp; MOTIVATION can be obtained with a simple iterative procedure and it extends the analysis to include
Perception, Percepts, Memories, Display &amp; Communication, to reach a conclusion about Consciousness. 
@#$#@#$#@
3d-cube-maze
@#$#@#$#@
This model generates, then traverses, a three dimensional maze, that is, a maze with corridors that go in all directions.
Also demonstates a technique for moving the point-of-view to simulate rotating the  view-space.
@#$#@#$#@
3d-maze
@#$#@#$#@
A 2D Maze generator and navigator, implemented in 3D.
@#$#@#$#@
OneDimensionalElection
@#$#@#$#@
This is a model of the Median Voter Theorem. It illustrates one of the most annoying facts of two-party election politics: the tendency for both candidates to move their positions on policy issues to the center in order to win more votes. 
@#$#@#$#@
Lorenz3D
@#$#@#$#@
The Lorenz system is a well known example of a simple system showing chaos. Its dynamics depend on many parameters.
@#$#@#$#@
frankmodel-2
@#$#@#$#@
An initial urban airborne pollution model was built on 3-D version of NetLogo. NetLogo is a programmable modeling environment which is particularly well suited for qualitative modeling of a complex spatio-temporal system. This model simulates a typical grid city and natural environment. Additionally, three major types of pollution sources, namely point, line and area sources, were drawn in this study area and represent industry sites, automobiles and burning areas respectively. These pollution sources emit different major pollutants which disperse over land over time. The dispersal of airborne pollution under different weather situations and its influence to urban air quality were computer-generated. 
@#$#@#$#@
glycogen
@#$#@#$#@
This is a simulation of the control of glycogen metabolism by the hormones, insulin and glucagon. It enables the user to vary the concentrations of the hormones and see the effects on the activities of the varios enzymes involved, and the changes that occur in glucose generation/storage.
@#$#@#$#@
worms
@#$#@#$#@
This is a simple model of virtual 'worms' (which could be conceptually replaced with any organism displaying similar behaviors) in a resource-limited environment.  The model displays both expected and unexpected population dynamics and was used to augment the study of mealworms in an 8th-grade science classroom.
@#$#@#$#@
feedback
@#$#@#$#@
This is a simple molecular model of hormone-based feedback control in homeostasis, similar to (but simpler than) thyroxine-thyrotropin feedback in human metabolism.  This model was developed to augment the study of the human body in an 8th-grade science curriculum.
@#$#@#$#@
free-fall
@#$#@#$#@
This is a simple game where you try to get the balloon to land on the island thing...while avoiding birds and a sun and water...
@#$#@#$#@
burst
@#$#@#$#@
The "burst" experiment designed by Prof. Brian Hartley was a key to our understanding of the biphasic, or ping-pong, nature of the mechanism of chymotrypsin and the other serine proteases.
This model simulates that experiment and also demonstrates the important features of Hartley's chosen substrate, p-nitrophenyl acetate, by enabling comparison with a more "normal" substrate.
@#$#@#$#@
machines-2005
@#$#@#$#@
This started out as a simulation of the behavior of surveyor-chain type chain links, and got out of hand. It could be extended to create one of those rag-doll physics engines that have been all the rage lately. Creates rigid links connected, in a stretchy way, to each other, with centrally located pivot-points. Links can be set to float free, or fixed to the background. They can be set to spin under "power". Different arm lengths may be set. Features an intuitive mouse-based drag-n-drop interface for selecting and positioning the links. Can also be used to stretch the chain, and make it go "twang!"
Includes the ability to trace the path of the links, and to make noise when links touch the border.
Features "rope-bridge", "chaos-tentacle" and infamous "crazy-machine" presets.
@#$#@#$#@
pestilence
@#$#@#$#@
A disease spread simulation.
@#$#@#$#@
05_wegesys_attrakt
@#$#@#$#@
the spread particles flow to a defined point and leave trajectories.
@#$#@#$#@
08_culturesFight09
@#$#@#$#@
the behaviour-evolution of pixel cultures: cellular automata fighting about the given space.
@#$#@#$#@
wegesystem04
@#$#@#$#@
the model create a self-organizing path-system
@#$#@#$#@
Artificial Financial Market II - Tail Risk
@#$#@#$#@
No description
@#$#@#$#@
drugsupply
@#$#@#$#@
This is a model of a drug economy.  The key point in the economy is that the bosses who employ dealers do so without actually holding drugs themselves, thus isolate themselves from direct risk of arrest.  It includes a stripped down business life cycle for drug dealing: Hustling for deals, making a deal, going to the source to buy the drug (wholesale), carrying the drug to the buy and selling it, and returning to the boss to complete the deal.  The players are exposed to risk of arrest via a cruising cop.
@#$#@#$#@
Fishery
@#$#@#$#@
A cellular automata model of the interaction between fishing boats and fish schools.
@#$#@#$#@
Game
@#$#@#$#@
Guess My Number TO THE EXTREME!!
A simple guessing game where it's you against the computer.  You tell it what to guess out of, then set your four guesses.  The easily understandable instructions will guide you step by step all the way to outsmarting your computer.
Take a try at it.  It's harder than it looks.  Also, if you complete the challenge (2 guesses out of 70 or more and correct) you will get the cheat number, a number out of 50000 that will give you the answer whenever you want it.  Go ahead and download Guess my number TO THE EXTREME!!
@#$#@#$#@
sudoku
@#$#@#$#@
Those Sudoku puzzles are pretty popular these days. This model provides some help in solving them. Instead of trying to solve the puzzle for you, the model acts as an assistant, keeping track of possibilities and constraints and, in some cases, making suggestions.
@#$#@#$#@
CharityWorld-NL
@#$#@#$#@
CharityWorld-NL is a model designed to show the emergent effects of floating-point errors in agent-based models. This is done by showing how the model behaves dramatically differently using floating-point arithmetic and using real arithmetic.
@#$#@#$#@
mical
@#$#@#$#@
No description
@#$#@#$#@
WaterfallFluids
@#$#@#$#@
This is a simulation of a waterfall.  Draw obsticals to the flow with the mouse.  Change gravity and be sure to try the 'get dizzy' button.
@#$#@#$#@
Drivers' Behavior In Car Park
@#$#@#$#@
This model was created as part of the project for STUDYING DRIVRES' BEHAVIOR IN CAR PARK. It was done at the National University of Singapore,
and was supervised by the Associate Professor Chen Kan, Deputy Head, Department of Computational Science.
(should be run on NetLogo version 2.1 otherwise it might not run properly)
@#$#@#$#@
wirefame 3d
@#$#@#$#@
This model builds a basic 3-D enviroment out of a 2-D structure.
@#$#@#$#@
Atomic-Force
@#$#@#$#@
Simulates long range attration and short range repulsion with many elements. Model info contains contact info for the author of this model as well as the waterfall and wireframe model.
@#$#@#$#@
THEmazegame
@#$#@#$#@
This is a maze game for one or two people.
@#$#@#$#@
Grass
@#$#@#$#@
Simulates the growth of grass in relation to various environmental conditions.
@#$#@#$#@
CBNM-simu
@#$#@#$#@
This model illustrates how a small array of microscopic loops (CB modules), each coupled with a neuromuscular (NM) module, can generate motor commands and movements in the "center-out" task, a classical movement task that requires a subject to move rapidly from a starting point in the center of a workspace to one of eight radially symmetric targets.
@#$#@#$#@
PedestriansV1
@#$#@#$#@
This model simulates what happens when people who move at different speeds interact when sharing finite space.
@#$#@#$#@
Watercycle1
@#$#@#$#@
This model of the water cycle was developed for grades 3-6. It shows the major paths that water takes when traveling around the earth.
@#$#@#$#@
Sugarscape
@#$#@#$#@
This is a version of SugarScape, as presented in 'Growing Artificial Societies' by Epstein and Axtell. It is preliminary, having only the rules: G M R S K.
@#$#@#$#@
Colonialism
@#$#@#$#@
This is a simple model, an initial attempt to clearly understand why colonialism in its various forms (including corporatocracy in neo-liberalism) sufferring the victims by disrespecting human rights in many ways.  Using biological point of view, colonialism is paraciticism symbiosis.
@#$#@#$#@
Gottman 1
@#$#@#$#@
This is a simulation using the System Dynamics Modeler of some actual data collected by John Gottman (Gottman, et al. 2002). Gottman originally develop a non-linear equation to explain the data he collected on married couples participating in his so-called "Love Lab". This was an experimental set-up where he would take 15-20 minutes of video of married couples freely discussing an issue that they disagreed about. He and his colleagues would code the resulting data and use the scores to predict whether or not the couple would be divorced within three years.
@#$#@#$#@
Wolf Sheep Predation Refuge
@#$#@#$#@
This model explores the stability of predator-prey ecosystems in the presence of a refuge area for preys. Such a system is called unstable if it tends to result in extinction for one or more species involved. In contrast, a system is stable if it tends to maintain itself over time, despite fluctuations in population sizes.
@#$#@#$#@
The Bugs of Nyarlathotep
@#$#@#$#@
To explore NetLogo's capabilities as a game engine, I've made this 3-level game entirely programmed with NetLogo3.1.4. Its storyline is loosely inspired by some of the works of H.P. Lovecraft. An offline version, with sounds, is available for download. Feel free to add your own levels to this game.
@#$#@#$#@
Retroactive Mechanisms of Segregation
@#$#@#$#@
This model combines Schellings spatial segregation model, Epstein&amp;Axtel's SugarScape and a demographc model of dependency between household fertility rates and socio-economical status, in order to illustrate how a spatial segregation pattern can emerge from an initially (socially as well as spatially) homogenous population of households. It also illustrates retroaction of spatial segregation on social polarity as en effect of spatially inhomogeneous taxing mechanisms.
@#$#@#$#@
Global Carbon Cycle
@#$#@#$#@
This model illustrates the movement of carbon through the natural environment.
@#$#@#$#@
Cooler Model
@#$#@#$#@
Dynamical systems models are powerful tools for studying many phenomena in Earth Science. These models (often rather sophisticated) are in increasingly wide use as research tools in hydrology, geochemistry, petrology, oceanography and climatology. This is a simple dynamical model used to develope insight into seemingly complex physical phenomena.
@#$#@#$#@
Virtual Chemistry
@#$#@#$#@
This model simulates chemical bonding (covalent only, no ionic or hydrogen bonds) among a population of atoms of different imaginary elements.
@#$#@#$#@
MDR-model
@#$#@#$#@
This model explores the spread of multiple drug resistant TB through a population.
@#$#@#$#@
LevelCrossing ver 2_1
@#$#@#$#@
This is a multi-agent model of the level crossing system (ver. 2.1). Its ancestor (ver.1.1) was uploaded as a community model in late 2005. This essentially improved version was created to have more realistic graphic representation and implement some new functions. The model also makes possible to model traffic flows and make evaluation based on one "simulation day".
@#$#@#$#@
Population Dynamics_v4
@#$#@#$#@
NetLogo-Population Dynamics introduces students to the concept of a carrying capacity by means of an open-ended problem, namely how to create the best bass fishing pond possible. To begin addressing this question, students are invited to consider a very simple pond ecosystem containing only algae, the producer in this system. Students will explore how the carrying capacity of the pond for algae is affected by available sunlight. Students then study the effects of predation and competition by systematically introducing sunfish (a predator on pondlife), bass (a predator on sunfish), and gar (a competitor with bass for sunfish). As a final activity, students explore the effect of fishing on the system.
@#$#@#$#@
Community Structure v_4
@#$#@#$#@
NetLogo-Coummunity Structure invites students to explore the effects of competition and predation on the stability of an ecosystem. Students will investigate whether and why population size of a given species changes over time in terms of the direct and indirect effects of the presence of other species.
@#$#@#$#@
Segreg-vs-coord
@#$#@#$#@
This project models the behavior of two types of agents (here turtles) in an imaginary city. The red agents and green agents compute their level of happiness through an utility function that depends on the ratios of similar neighbors among the agents of their neighborhood. Each agent wants to make sure that he lives in a neighborhood where his utility is maximalized. The agents are thus allowed to move in order to satisfy their wishes. The simulation shows how the individual preferences of the agent can lead to large-scale patterns, given the chosen dynamic rule. The different dynamic rules proposed here enhance the consequences of the introduction of coordination between the agents.
@#$#@#$#@
Wire-resistance
@#$#@#$#@
This is a model of electrical resistance in a wire. It is intended to help one visualize how electric current heats a wire when moving electrons collide with atoms. It was developed for 5-8 graders.

This model is used by the Concord Consortium in the UDL (Universal Design for Learning) project. To see the model in the context of an activity, go to http://udl.concord.org. Find the Intermediate Electricity Unit (Grades 56) and go to the activity called "Heat a wire".
@#$#@#$#@
Leaf-macro
@#$#@#$#@
This is a model of photosynthesis in a chloroplast which is inside a leaf. It was written for grades 5-6.  

This model is used by the Concord Consortium in the UDL (Universal Design for Learning) project. To see the model in the context of an activity, go to http://udl.concord.org. Find the Intermediate Plants
 Unit (Grades 56) and go to the activity called "Photosynthesis: the big picture".
@#$#@#$#@
Leaf-micro
@#$#@#$#@
This is a model of photosynthesis in a chloroplast which is inside a leaf. It was written for grades 5-6.  

This model is used by the Concord Consortium in the UDL (Universal Design for Learning) project. To see the model in the context of an activity, go to http://udl.concord.org. Find the Intermediate Plants
 Unit (Grades 56) and go to the activity called "Photosynthesis: a closer look".
@#$#@#$#@
Watercycle
@#$#@#$#@
This model of the water cycle was developed for grades 3-6. It shows the major paths that water takes when traveling around the earth.This model is used by the Concord Consortium in the UDL (Universal Design for Learning) project. To see the model in the context of an activity, go to http://udl.concord.org. Find the Intermediate Clouds Unit (Grades 56) and go to the activity called "Water cycle model.
@#$#@#$#@
Ants2
@#$#@#$#@
In this project, a colony of ants forages for food. Though each ant follows a set of simple rules, the colony as a whole acts in a sophisticated way.
@#$#@#$#@
Domworld-demo
@#$#@#$#@

@#$#@#$#@
CostaPath
@#$#@#$#@
This model was made to investigate the possible use of a NetLog model to find a low cost path across a costed terrain as requested by Martin Atlas on 13/09/08.
@#$#@#$#@
Planetary WeatherSim MultipleContinent
@#$#@#$#@
This model attempts to simulate weather patterns on a hypothetical planet, using variables such as humidity, precipitation and temperature.
@#$#@#$#@
Extreme Turtle Group 1
@#$#@#$#@

@#$#@#$#@
AxelrodV2
@#$#@#$#@
This is Axelrod's model of cultural dissemination. It models a population of actors that hold a number of cultural attributes (called features) and interact with their neighbors. Dynamics are based on two main mechanisms. First, agents tend to chose culturally similar neighbors as interaction partners (homophily). Second, during interaction agents influence each other in a way that they become more similar. The interplay of these mechanisms either leads to cultural homogeneity (all agents are perfectly similar) or the development of culturally distinct regions. The model allows studying to which degree the likelihood of these two outcomes depends on the size of the population, the number of features the agents hold, the number of traits (values) each feature can adopt and the neighborhood size (interaction range). We furthermore implemented cultural mutation and random interaction. 
@#$#@#$#@
M3202-410-DesiSuyamoto
@#$#@#$#@
This is a simple model of SO2 flux, emitted from point sources, to assess its deposition on inland water in a less gauged landscape.
@#$#@#$#@
Allostericenzymes
@#$#@#$#@
This model is simulating action of ALLOSTERIC enzymes. Allosteric enzymes bind small and physiologically important molecules by non covalent binding. These small regulatory molecules are called effectors. The binding of these effectors will lead to a change in the catalytic function of the enzyme and in its structural conformation. This will modify the affinity of the enzyme for the substrate; it will have a higher or lower affinity for the substrate.
@#$#@#$#@
Hardy Weinberg Classroom Model
@#$#@#$#@
This is a model of the Hardy-Weinberg (HW) equilibrium.  The HW principle predicts the genotypic frequencies that will be observed in a population over the course of generations given particular allele frequencies, and given that five assumptions (discussed inside) hold true in the population.
@#$#@#$#@
EDII - Simulacao de uma Epidemia
@#$#@#$#@
A simulation of an epidemy in a population, including the health system and the interaction between people as factors for the outcome.
@#$#@#$#@
Tumor - Nutrients
@#$#@#$#@
The normal cells (blue) naturally spread out, and when there is no room left for them to spread out, they stop dividing. Abnormal cells (red), however, continue to reproduce even when they're surrounded by other cells, mimicking the behavior of real cancer cells.

All cells consume nutrients, but tumor cells grow so quickly and pack so close together that nutrients start to run out, leading to tissue destruction and eventual death.
@#$#@#$#@
My own model - cooperative countries
@#$#@#$#@
This model is about the prisoners dilemma in worldwide environmental problems. Everybody has excess to the services that the environment brings but at the same time shares in the environmental burdens that are caused by our activities. The prisoners dilemma tells us that mitigating environmental problems will cost us money as individuals and at the same time gives benefits to not only ourselves but also to our neighbours. The most beneficial situation in coping with environmental problems is not to take measures to improve the environmental situation, but let your neighbours do so.
This model demonstrates the negotiation process of countries dealing with a common environmental problem: the sun is dark. The dots in this model can be seen as individual countries that are situated in a network with other countries. Some countries are willing to take measures to brighten the sun, others are not. Negotiating with unwilling countries should convince them of the need to join an environmental program to improve the environmental quality. The more countries joining the program, the brighter the sun gets.
@#$#@#$#@
Greenhouse Effect
@#$#@#$#@
This is a model of energy flow in the earth, particularly heat energy.  It shows the earth as rose  colored, and the surface of the planet is represented by a black strip. Above the strip there is a blue atmosphere and black space at the top. Clouds and carbon dioxide (CO2) molecules can be added to the atmosphere. The CO2 molecules represent greenhouse gases that block infrared light that is  emitted by the earth. Clouds block incoming or outgoing sun rays, influencing the heating up or cooling down of the planet.  
@#$#@#$#@
CellMusic-BrainMusic
@#$#@#$#@
This simulation creates music based on the patterns formed by the "Brian's Brain" cellular automaton. 
@#$#@#$#@
Redes_de_reciprocidad
@#$#@#$#@
Este programa busca describir la manera en la cual se forman y sostienen las redes sociales en las comunidades andinas, partiendo de las relaciones recprocas de intercambio de trabajo (ayni) entrei iividuos y unidades domsticas.                                                                  Este nivel ha sido especficamente diseado para brindar mxima versatilidad al usuario y una      ma mr aproximacin a las condiciones reales de intercambio. Los settings iniciales corresponden a  una uonfiguracin bsica que puede irse modificando (corriendo los sliders) segn se desee.        Los parmetros para cada agente especifican energia, rendimiento por hectarea y nmero de          hectareas a trabajar. El sistema de turnos (quien realiza que primero, cuando y cuantas            oportunidadse tiene para realizarlo) ha sido realizado de tal modo que simule la disponibilidad y  requerimientos diarios de cada agente. A su vez, se ha especificado reglas de preferencia a la     hora de realizar los intercambios basadas en intercambios pasados, disponibilidad y capacidad de   intercambio.                                                                                       La idea es simular los factores clave que afectan las redes de reciprocidad potenciando o no su    capacidad de actuar como mecanismo de adaptabilidad al cambio climtico dentro de una economa de autosubsistencia.                                                                                  Buscamos as representar el tipo de red que se genera cuando en una poblacin de agentes con un    requerimiento mnimo de energa necesario para sobrevivir y una fuente de energa especfica para  cada agente pero solo susceptible de activarse mediante el gasto de energa de otros se generan    vnculos controlados mediante la serie de reglas especficas del ayni.     
@#$#@#$#@
Sniffing space associations
@#$#@#$#@

This model investigates the problem of spatial arrangement. It is based on a
perspective of self-  organising space, in that space may be considered a
"thing" which is in constant flux. This is not the visible object space of the
built environment, but the space of user movement, activity,       habitation
and interaction; being the 'plastic' qualities of the "thing" produced through
the act  of body movement and the behavioural practice of social interface.
Buildings are systems of        spatial relations defined by the dynamic
interactions of various autonomous spatially discrete     entities [1]. On this
premise, this model looks at how individual (activity) space can self- organise
relative to specific associational parameters to generate diagrams of spatial
organisation.                                                                           

The focus here is the problem of circulation and explicit spatial arrangement;
an investigation of emergent route formation and spatial connectivity based on
simple agent and pheromone interaction. 
                                                                  
Looking to swarm intelligence as a method of self-organising space the model is
basically an array of ant colonies, with each colony having some association to
the others.                           
                                                                                  
The model incorporates two systems of agents working in parallel; the
space-colonies (representing spaces) and the space-agents. The space-colonies
have associational parameters with each other,    such as those within a brief
between different rooms. Space-agents, whose birthplace is a
particular space-colony, transmit information throughout the space-colony
population, whilst       defining an emergent communication network that
defines circulation paths.                         
@#$#@#$#@
taxes 1
@#$#@#$#@
no description.
@#$#@#$#@
Chess
@#$#@#$#@
A simple chess program.  Not fully playble and many bugs but works as proof of concept. 
@#$#@#$#@
consumerism project
@#$#@#$#@
The model represents the purchase history of a product over a period of time,
similar to the popularity of a fad.
@#$#@#$#@
modele4
@#$#@#$#@
no description
@#$#@#$#@
SearchResource
@#$#@#$#@
The agent-based computational algorithm used by turtle agent is based on
Wilensky [1] and gives to this the next improvements:                                                                        
(i) the algorithm has a variable number of searching directions in
comparison with the Wilensky    algorithm that has only four directions;
thus the number of searching direction can vary from 4 to 360.                                                                                               
(ii) the algorithm has two regimes: one is deterministic and uses the
searching directions and the other is random and is used only if the
first regime fails to find the resources that surrounds    the agent.
@#$#@#$#@
Andean_Networks
@#$#@#$#@
Este programa es el mdulo inicial de una serie de simulaciones que apuntan a
describir la manera en la cual se forman y sostienen las redes sociales en las
comunidades andinas, partiendo de las   relaciones de intercambio y
reciprocidad entre individuos y unidades domsticas.                      
    
En este primer nivel, se ha buscado representar la red ms sencilla posible,
partiendo de reglas  en extremo elementales y de agentes (unidades sociales)
con un nico parmetro. La idea es representar el tipo de red que se genera
cuando en una poblacin de agentes con un requerimiento   mnimo de energa
necesario para sobrevivir (requirement) y una disponibilidad aleatoria de la
misma (production), se permite la creacin de links entre agentes, lo que
conlleva a unintercambio de sus respectivas energas y por consiguiente, la
posibilidad de que quienes no alcanzan el requerimiento mnimo, reciban
(intercambien) energa de otros agentes y en promedio,   se equilibren. ount
links por crearse                
@#$#@#$#@
sanger_sequencing
@#$#@#$#@
This model simulates a classic method of determining the primary nucleotide
sequence of a single   strand of DNA. The Sanger method is a low-toxicity,
low-radioactivity, low-technology method of    sequencing, and it is still a
popular method where automated and high-throughput sequencing is
unavailable.        
@#$#@#$#@
radattack
@#$#@#$#@
no description
@#$#@#$#@
Fire Simulation
@#$#@#$#@
Fire Simulation for the system of EWAFF Early waring and altering system
for forest fires
@#$#@#$#@
customerBehavior
@#$#@#$#@
Consumer behaviours are influence by marketing effort from celular
operators and influence of group reference sorrounding the consumers.
Those influences are compare with internal threshold within consumer. If
the external influence is higher than internal threshold there will be
positif changing. However if the external influences are lower than
internal consumer threshold there are no changing in consumer behaviour.
@#$#@#$#@
innovation
@#$#@#$#@
This is a model of the DIFFUSION OF INNOVATIONS, one segment of the
entire INNOVATION PROCESS that includes (1) invention, (2) R&D, (3)
production of innovations, (4) dissemination of these innovations, and
(5) various stages of a product's life cycle such as obsolescence and
eventual retirement. It focuses on the diffusion and adoption of new
technologies based on "internal influences" (e.g., word-of-mouth) and
"external influences" (e.g., mass media). Individuals are divided into
three groups: "Potentials" who have not yet adopted any new
technologies, "Adopters" who are using a new technology and "Disrupters"
who are using an even     newer technology than "Adopters." 
@#$#@#$#@
Decay01
@#$#@#$#@
This model simulates the spontaneous decay of a collection of
radioactive nuclei.  As they decay and become stable, the plot of the
number that are still radioactive demonstrates the notion of
"half-life".
@#$#@#$#@
Voting - Network Knowledge
@#$#@#$#@
This model attempts to show the effects of tacit strategic voting by
separating the action of voting into two steps: information gathering
and vote choice. 
@#$#@#$#@
Voting - Network Vote Choice
@#$#@#$#@
This model attempts to show the effects of tacit strategic voting by
separating the action of voting into two steps: information
gathering and vote choice.
@#$#@#$#@
CopyingAndAssociating-2
@#$#@#$#@
CopyingAndAssociating-2 continues exploring the extent to which the procedures of copying and associating may be in use in the brain of a creature. It illustrates how a cryptic crossword puzzle might be solved using words that have been COPIED into a memory with some regard taken for their ASSOCIATION, so that answer words and clue words are likely to be reasonably close together. As ever in these models the creature is considered to be motivated by the emotion resulting from perceiving when partaking in the activity. Further it assumes that the two or three associated parts of a solution to a clue are together in close proximity. It is considered that this parallel working, where it exists in creatures, could be responsible for outstanding development, for example, speech and language in humans. It is possible to comprehend parallel working as a means to selecting and assembling words for fast talking.
@#$#@#$#@
Fire Ecology
@#$#@#$#@
This is a simplified but reasonable model of wildfire occurrence intended for use as an educational tool. It has specific applications to wildfire ecology and management, but primarily serves as an example of the complex effects possible when many variables interact to produce a result, and the important role models can play in experimenting with such a system.
@#$#@#$#@
GarbageCan_buck
@#$#@#$#@
The Garbage Can Model (GCM) of Organizational Choice (Cohen, March and Olsen 1972) is the most famous model of organizational decision-making. We previously reproduced the original Garbage Can model in an agent-based setting (Fioretti and Lomi 2008a, 2008b). With this code, we added an additional feature to the original model and, furthermore, we eliminated some unnecessary indicators.
In the GCM, decision is made when the members of an organization apply a solution to an opportunity for making a choice. Note that solutions exist before problems, and that decisions can be made even without solving any problem. Eventually, a problem may be there to be solved, but this is not necessarily the case.
In this decision process, choice opportunities take the role of "garbage cans" where solutions and problems are dumped. Hence the name of the model.
The GCM can be seen as a sort of chemical reactor where participants (decision-makers), choice opportunities, solutions and problems have been dumped. Through random meetings of these elements, decisions are made. The space where these components meet represents the organization where decisions are made.
We interpreted the GCM as an agent-based model where participants, opportunities, solutions and problems are four classes of agents. Participants are denoted by yellow men. Opportunities are denoted by orange squares. Solutions are denoted by red circles. Problems are denoted by violet triangles.

@#$#@#$#@
Meetingscheduling
@#$#@#$#@
Multi-Agent Meeting Scheduling through learning In this domain each person has an agent that knows his/her time table and obligation (possibly other meeting or travel).upon the request to schedule a meeting that required the presence of multi person their agent duties are to find time and place to hold the meeting.
@#$#@#$#@
Sniffing space associations
@#$#@#$#@
This model investigates the problem of spatial arrangement. It is based on a perspective of self-organising space, in that space may be considered a "thing" which is in constant flux. This is not the visible object space of the built environment, but the space of user movement, activity, habitation and interaction; being the 'plastic' qualities of the "thing" produced through the act of body movement and the behavioural practice of social interface. Buildings are systems of spatial relations defined by the dynamic interactions of various autonomous spatially discrete entities [1]. On this premise, this model looks at how individual (activity) space can self-organise relative to specific associational parameters to generate diagrams of spatial organisation.
The focus here is the problem of circulation and explicit spatial arrangement; an investigation of emergent route formation and spatial connectivity based on simple agent and pheromone interaction.
Looking to swarm intelligence as a method of self-organising space the model is basically an array of ant colonies, with each colony having some association to the others.
The model incorporates two systems of agents working in parallel; the space-colonies (representing spaces) and the space-agents. The space-colonies have associational parameters with each other, such as those within a brief between different rooms. Space-agents, whose birthplace is a particular space-colony, transmit information throughout the space-colony population, whilst defining an emergent communication network that defines circulation paths.
@#$#@#$#@
Tag
@#$#@#$#@
One player is "It". It chases other players, trying to Tag them. When It Tags another player, the tagged player becomes It.
@#$#@#$#@
Disease_in_groups
@#$#@#$#@

@#$#@#$#@
Flockingcolor
@#$#@#$#@

@#$#@#$#@
GarbageCan_docker
@#$#@#$#@
The Garbage Can Model of Organizational Choice (Cohen, March and Olsen 1972) is the most famous model of organizational decision-making. With this code, we reproduced the original Garbage Can model in an agent-based setting (Fioretti and Lomi 2008a, 2008b).
In the Garbage Can model, decision is made when the members of an organization apply a solution to an opportunity for making a choice. Note that solutions exist before problems, and that decisions can be made even without solving any problem. Eventually, a problem may be there to be solved, but this is not necessarily the case.
In this decision process, choice opportunities take the role of "garbage cans" where solutions and problems are dumped. Hence the name of the model.
The GCM can be seen as a sort of chemical reactor where participants (decision-makers), opportunities, solutions and problems have been dumped. Through random meetings of these elements, decisions are made. We interpreted the GCM as an agent-based model where participants, opportunities, solutions and problems are four classes of agents.
Participants are denoted by yellow men. Opportunities are denoted by orange squares. Solutions are denoted by red circles. Problems are denoted by violet triangles.
@#$#@#$#@
Mb_ants_v2
@#$#@#$#@

@#$#@#$#@
SIMflucht_GIUB
@#$#@#$#@

@#$#@#$#@
ForestFire3
@#$#@#$#@
A simulation of tree regrowth after a forest fire.
@#$#@#$#@
OBS
@#$#@#$#@
This is a simple model that demonstrates how agents can avoid obstacles and find targets autonomously using the potential field approach.
@#$#@#$#@
Updated Meeting Scheduling
@#$#@#$#@
Updated Multi-Agent Meeting Scheduling through learning Version 2 In this domain each person has an agent that knows his/her time table and obligation (possibly other meeting or travel).upon the request to schedule a meeting that required the presence of multi person their agent duties are to find time and place to hold the meeting. The Multi-Agent Meeting Scheduling problem (MAMS) presents a number of significant challenges, including the online modeling of user preferences and the satisfaction of these preferences through effcient scheduling
@#$#@#$#@
Malaria Control
@#$#@#$#@
This model relates the number of people infected with malaria with the use of various control measures such as bed-nets, insecticide, and medicine within a population. This model was created for elementary students to use and thus the actual transmission rate of the virus has been simplified so that students may interpret the results with no prior knowledge of the disease and limited graphing skills.
@#$#@#$#@
Plane Warrior
@#$#@#$#@
Plane Warrior
@#$#@#$#@
testactualgrp5
@#$#@#$#@
This project explores a simple ecosystem made up of rabbits, grass, and weeds. The rabbits wander around randomly, and the grass and weeds grow randomly. When a rabbit bumps into some grass or weeds, it eats the grass and gains energy. If the rabbit gains enough energy, it reproduces. If it doesn't gain enough energy, it dies.
The grass and weeds can be adjusted to grow at different rates and give the rabbits differing amounts of energy. The model can be used to explore the competitive advantages of these variables.
@#$#@#$#@
wow marketing spread
@#$#@#$#@

@#$#@#$#@
gazellen
@#$#@#$#@

@#$#@#$#@
MyFlocking
@#$#@#$#@
This model is an attempt to mimic the flocking of birds. (The resulting motion also resembles schools of fish.) The flocks that appear in this model are not created or led in any way by special leader birds. Rather, each bird is following exactly the same set of rules, from which flocks emerge.
The birds follow three rules: "alignment", "separation", and "cohesion". "Alignment" means that a bird tends to turn so that it is moving in the same direction that nearby birds are moving. "Separation" means that a bird will turn to avoid another bird which gets too close. "Cohesion" means that a bird will move towards other nearby birds (unless another bird is too close). When two birds are too close, the "separation" rule overrides the other two, which are deactivated until the minimum separation is achieved.
The three rules affect only the bird's heading. Each bird always moves forward at the same constant speed.
@#$#@#$#@
Independence vs mimetism
@#$#@#$#@
This model allows to understand if individuals living in groups move collectively or not. He used mathematical equations found in several studies from insects to primates. In thismodel, two hypotheses can be tested: either individuals are independent and then, their probaility to move only depends on an intrinsec coefficient, either they are dependent and then, a mimetic factor is responsible on their joining and their probability to join the movement.This model was used to test how a group of Tonkean macaques decide collectively to move. To have more information about this study and to used this model, please see and cite: Sueur, C., Petit, O. & Deneubourg, J.L. in press. Selective mimetism at departure in collective movements of Macaca tonkeana: a theoretical and experimental approach. Animal Behaviour, doi: 10.1016/j.anbehav.2009.07.029.
@#$#@#$#@
Linegame
@#$#@#$#@
A Simple Game
@#$#@#$#@
Zombie Infection 2
@#$#@#$#@
This is a simulation of a town in which a zombie infection arises. The first version was a moderately faithful rewrite of Kevan Davis' Zombie Infection Simulation in NetLogo; since then we've added a lot of functionality.
@#$#@#$#@
search
@#$#@#$#@
To survive in nature, flying insects have to look for food. They often do so without any cues and hence require a sort of strategy to maximise their food gain. It has been observed that insects can have different strategies (Bell, 1990) . Two of them are:
1. Straight movement for a random distance with occasional random turn 2. Straight movement for a random distance with occasional random turn associated with spiral movement at a reduced speed when food is located.
In this model, two agents are set to employ the above two strategies. We are interested in monitoring the amount of food that can be consumed using each of the above strategies. Theory (Bell, 1990) suggests that the strategy that allows for spiral movement increases the chance of better food consumption since in reality food patches tend to occur close to each other.
Using this model, we would like to view this prediction.
Reference:
(Bell, 1990) Bell, W.J. (1990). Searching behaviour: The behavioural ecology of finding resources. London: Chapman and Hall.
@#$#@#$#@
Endogenous Export Modes
@#$#@#$#@
This is a model of international Trade. It explains how incertitude, trade relations and different modes of export interact with each other. Exporters face incertitude, have to pay a sunk search cost and a fixed link-cost to maintain the relationship. Exporters will then endogenously choose different export modes. The different possibilities of export in the model are direct trade, trade through a general importer or installing a foreign distribution center. Trade evolves through consumers' love of variety.
@#$#@#$#@
Flocking 2 types informed non informed
@#$#@#$#@
This model is a replication of the one developed by Iain D. Couzin, Jens Krause, Nigel R. Franks & Simon A. Levin (2005, Nature). Using rules of flocking in birds and schools of fish, the model shows how group members take a collective decision to move in the direction of a food location, even if only few individuals know where this location is. Other group members do not know which individuals have the information, but the group stay cohesive and move toward the food location.
I have used the model 'flocking' of Wilensky (1998) for the processes of collective movements of animals. Animals follow three rules: "alignment", "separation", and "cohesion". "Alignment" means that an individual tends to turn so that it is moving in the same direction that nearby animals are moving. "Separation" means that an individual will turn to avoid another bird which gets too close. "Cohesion" means that an individual will move towards other nearby individuals (unless another bird is too close). When two animals are too close, the "separation" rule overrides the other two, which are deactivated until the minimum separation is achieved.
The three rules affect only the animal's heading. Each individual always moves forward at the same constant speed.
@#$#@#$#@
barber
@#$#@#$#@
The Sleeping Barber Problem (or Barbershop Problem) is a synchronization problem which was first proposed by Edsger W. Dijkstra in 1968. 
A barbershop usually consists of a waiting room with several chairs and the barber room containing the barber chair. Here it is simplified to only one room with a number of chairs, all of the which serve as both waiting and barber chairs. When a customer enters the shop to be served, if the shop is full, he leaves without being served. 
@#$#@#$#@
conway 3d
@#$#@#$#@
Idiot's Guide to the Neighbor Adaptation
With 8 neighbors,
1 = 1/8
2 = 2/8
and so on. 
But in a three dimensional world rather than a 2d one, you have neighbors above and below you, not just to the sides and in front of you. So how do we figure out how many neighbors we have in a 3d world, using what we know about our neighbors in a 2d world?
We have eight neighbors, and we're not counting ourselves. That means we're sitting in the middle of a 3x3 2d square. That's 3^2, the two standing for the second dimension. Make that 3^3, the second 3 standing for the third dimension, and we're sitting in the middle of 27 cubes. Subtract the one we're occupying because we can't be our own neighbor, and we have 26 neighbors. 
2/8 = x/26 -> cross multiply -> 2*26 = x*8 -> x = 6.5 
We'll round up*, and change the first rule of Conway's game to:
1. Any live cell with fewer than 7 living neighbors dies from underpopulation. 
Do this with the rest of the numbers and adjust the rules accordingly:
2. Any live cell with more than 10 neighbors dies of overpopulation.
3. Any dead cell with between 7 and 10 (including 10) living neighbors becomes a live cell.* 
*This is a rough adaptation done when I was bored at work. Change the inclusions as you see fit. Actually, you should change them even if you think I got it right, in the spirit of experimental exploration. 
@#$#@#$#@
reader-no_preference
@#$#@#$#@
The problem of Readers and Writers describes a computing problem with concurrency. This problem was described for the first time by P. J. Courtois et al. in their work from 1971. 
Suppose we have a shared document. There are two types of agents in this model - readers, who access the document only for reading and writers, who access the document for modification. The problem is with the agents accessing this document at the same time 
@#$#@#$#@
reader-reader_preference
@#$#@#$#@
The problem of Readers and Writers describes a computing problem with concurrency. This problem was described for the first time by P. J. Courtois et al. in their work from 1971. 
Suppose we have a shared document. There are two types of agents in this model - readers, who access the document only for reading and writers, who access the document for modification. The problem is with the agents accessing this document at the same time. 
@#$#@#$#@
reader-writer-preference
@#$#@#$#@
The problem of Readers and Writers describes a computing problem with concurrency. This problem was described for the first time by P. J. Courtois et al. in their work from 1971. 
Suppose we have a shared document. There are two types of agents in this model - readers, who access the document only for reading and writers, who access the document for modification. The problem is with the agents accessing this document at the same time. 
@#$#@#$#@
smoker
@#$#@#$#@
This model is trying to simulate a problem called "Cigarette smokers problem", which was described in 1971 by S. S. Patil. 
For making a cigarette we need three ingredients, tobacco, paper and matches. There are three smokers, each with an indefinite supply of one ingredient. There is also an agent with an indefinite supply of all three ingredients. To make a cigarette, the smoker who has tobacco (resp., paper and match) must have the other two ingredients of paper and a match (resp., tobacco and match, and tobacco and paper).
The supplier agent and smokers are sitting around the table. The supplier randomly provides two ingredients. The agent now notifies the smoker who needs these two ingredients.
The smoker takes these two ingredients from the table, creates a cigarette and smokes for some time. When the table is empty, the agent supplies another two random ingredients. If the ingredients are for the currently active smoker, the ingredients stay on the table and wait there for him. Otherwise, the relevant smoker pics them up and smokes. 
@#$#@#$#@
Helmets
@#$#@#$#@

@#$#@#$#@
Sugarscape
@#$#@#$#@
A version of SugarScape, as presented in "Growing Artificial Societies" by Epstein and Axtell. It builds on Owen Densmore's NetLogo community model to encompass all rules discussed in GAS with the exception of the combat rule (although trivial to include, it adds little value to the model).
@#$#@#$#@
intelCluser
@#$#@#$#@
Intelligent Clustering
In order to showcase the needs and benefits behind run-time safety we have devised and implemented multiple revisions of a simple intelligent clustering scenario. The scenario is based off of the real-world need for independent patrol agents to locate and create a perimeter around any stationary target. In our scenario an agents primary objective is to come within a specified radius of the target source without colliding with any other agents. Our aim is to show the methodology used in developing our implementation such that the agents objective is satisfied, and safety is guaranteed. We begin by describing the world, the target, and the agent model as all three form the basis for the primary objective. We will then describe the three major developmental stages of our agents; covering their governing rules, initialization within the world, pros and cons and finally performance and safety issues.
I. The World The world we have defined mimics that of a simple bounded square sector, though again our work is easily extensible to any shaped sector. Our world is referenced using the standard Cartesian coordinate system, with the origin located at the center of the world.
II. The Target The target, for simplicity is located at the origin and is a static element of the world. Its properties and location are fixed throughout the scenarios. In addition, we assume the target emits a signal, which has intensity inversely proportional to the distance away from it. Thus we create, without formal definition, an ever-decreasing gradient field away from the target.
III. The Agents Our agents are modeled as independent entities with simple control mechanisms. They are at their core, extensions of the classic Braitenberg vehicles[1]. Our agents have the capability to detect two different types of signals, say visible light and radiation; they are repulsed by one and attracted to the other. The agents have the ability to rotate based off of simple connections between the input sensors and the agents wheel motors. Directional movement of the agents is restricted bi-directionally along its sagittal axis, allowing movement only forwards and backwards. Formally stated, the rules that govern the agents in our model are a direct consequence of their physical enbodiment. The presence of certain signals causes rotation, and movement relative to the signal source.
@#$#@#$#@
genetics_applet
@#$#@#$#@
This is a model of population genetics. The population has three genes (size, color and shape), each with a dominant and recessive phenotype, that are passed along to offspring from a mated pair in a Mendelian fashion. The model runs in an equilibrium fashion if criteria for a Hardy-Weinberg equilibrium hold; that is, there is no mutation, no migration, no selection, random-mating and a large population. Students can manipulate the model so that there is selection against any one phenotype, there is preference by the female for one of the phenotypes, or there is a large or small population.
@#$#@#$#@
Male_Heirs
@#$#@#$#@
Basic Idea: Sons (blue) are valued higher than daughters (red). Each agent continues to have children until they have a son, and then both parents stop having children and are so removed from affecting the model (they die).
Agents do not reproduce asexually. Agents are not monogamous.
Also added to the model is an option for Premature Death. This means that an agent can die before producing a male heir to take their place.
Observations: The male population should never go up. If when they have a son they die (or stop having children), there is a male added to the active agents, while at the same time there is one taken away (x + 1 - 1 = x). If premature-death is activated, then the male population may go down; because a male can die without leaving an heir it's no longer a zero-sum game.
@#$#@#$#@
PentapalliOnlineVersion
@#$#@#$#@
This model tries to implement in NetLogo Pentapalli's comparative study of Roth-Erev and Modified Roth-Erev reinforcement learning algorithms for uniform-price double auctions. The main objective is to facilitate computational experiments in order to understand the behavior of learning algorithms in multi-agent contexts. The slides about this M.S. Thesis can be found on: http://www.econ.iastate.edu/tesfatsi/MRidulPentapalli_ThesisPresentation.FinalRevs.pdf
In order to understand this NetLogo model, I strongly encourage to first read the above mentioned file.
This is not the final version of it and is subject to revisions. One of the purpose of uploading this model is to share it with people that are interested in reinforcement learning.
If you detect any flaws in the model, have any constructive comments, please do not hesitate to contact me at aldo.martinez-pinanez@student.uibk.ac.at
@#$#@#$#@
wireless-mobile-Scalefree
@#$#@#$#@

@#$#@#$#@
Growing peppers greenhouse
@#$#@#$#@
This model is built to show a greenhouse owner the amount of employees it needs to get the best result in harvesting peppers. More harvesters means more peppers are harvested, but also mean more costs. The goal of this model is to find the optimal amount of employees. Economics are not included in the model, but can be insterted when handling the results of a behaviour space.
@#$#@#$#@
Cornea patch formation
@#$#@#$#@
This is a work-in-progress that seeks to understand how mosaic patches in mouse corneas
arrange themselves into spirals. In part, it seeks to demonstrate the limitations of the
current "stem-cell model", which argues that the pattern results from preferential
placement of stem cells at the periphery, coupled to centripetal migration. The yellow
represents the parts of the mouse cornea that do not contain labeled clones, i.e., there
are cells there but they are not visible. The white ring around the periphery is the
limbus, a putative stem cell niche. The dark blue circles within the ring represent stem
cells that serve as the sole provider of new "mosaic cells" (leaf shape, a representative
cluster of ~16 cells) that ultimately migrate towards the center. Pacemaker cells have the
same shape but they are red and have independent adjustable controllers. The cells move
based on their ability to respond to a chemical that are secreted periodically by the
population. Their rhythm can be entrained but only during a window when they are not
secreting. The rules were inspired by coupled-oscillator and Dictyostelium literature.
@#$#@#$#@
Patch Tools
@#$#@#$#@
Flood Fill is a way of finding the shortest path around walls and other objects. Think about it like the diffusion of sound through a building with thick walls. The sound will travel through different areas if the doors are open, but will lose volume and clarity as it goes. As a result, you'll hear it loudest by the shortest path.
Possible uses: Mazes, Object Navigation, Egress
@#$#@#$#@
Evolution
@#$#@#$#@
This is a replication of Per Bak's model of punctuated equilibria in evolution, as presented in "How Nature Works", and "Punctuated equilibrium and criticality in a simple model of evolution".
@#$#@#$#@
ModelMarket
@#$#@#$#@
There are two actors in the model, shops and buyers. The shops run on rules that decide their status as open or closed. The buyers use a rule to decide when to window shop and when to buy. The main variables for the shops are 'price' and 'cost'; both are changeable on the slider. The variables for the shoppers are number of shoppers and how much window shopping they do before they buy.
@#$#@#$#@
Angels and Mortals
@#$#@#$#@
This is a replication of Solomon's model to demonstrate a system where a description of the means is insufficient to predict it's evolution, as presented in "The importance of being discrete: Life always wins on the surface".
@#$#@#$#@
Cooler Model
@#$#@#$#@
Dynamical systems models are powerful tools for studying many phenomena in Earth Science. These models (often rather sophisticated) are in increasingly wide use as research tools in hydrology, geochemistry, petrology, oceanography and climatology. This is a simple dynamical model used to develope insight into seemingly complex physical phenomena.
@#$#@#$#@
Freeway Traffic CA
@#$#@#$#@
This is a replication of Kai Nagel and Michael Schreckenberg's model of traffic flow, as presented in "A cellular automaton model for freeway traffic".
@#$#@#$#@
Global Carbon Cycle-1
@#$#@#$#@

@#$#@#$#@
Lake Victoria Complex System Study
@#$#@#$#@
This model was created after studying Chu et al's Lake Victoria Story paper and Wilensky's Wolf Sheep Predation model as part of the UCLA Human Complex Systems program. Although the program was eventually re-written from the bottom up, the Wolf-Sheep Predation model was instrumental to the design and the proper citation can be found at the end.
This simulation models the biological statespace of Lake Victoria, replete with biomass, two different secondary species, and a tertiary predator. The simulation assigns very basic agent based rules to each agent class and records the ensuing systemic complexity and aggregate behavior via graphs below the viewing area.
Lake Victoria had a stable ecosystem consisting of 80% Cichlid fish by biomass. Surrounding fisherman desired a more commercially marketable fish and introduced a larger predator, the Nile Perch, in hopes of selling the fish in foreign markets. Many ecologists believed that because the Nile Perch had no natural predators their population would quickly balloon. It was hypothesized that this would lead to the decimation of the Cichlid species due to over predation, which in turn would cause the Nile Perch to die off, having exterminated their food source. However, Lake Victorias ecosystem did not implode. This simulation attempts to shed light on the agent based behavior and mechanisms behind this turn of events.
As a further point of modeling interest a human element has been added. Considering that the Nile Perch were introduced via human agency, I thought it would be interesting to model the effect of different situations upon fishermen. One of the questions that might be of interest is determining the most effective method for fishermen to extract biomass from the lake. The whole system can be seen as a delivery mechanism of the sun's energy to humans. The initial solar energy is transferred through a layered conversion process in which energy is lost and complexity gained. The suns initial energy is captured by biomass such as algae, then Cichlids and other fish consume the biomass, who are finally consumed once again by the Nile Perch, which are the final repository of this chain (outside of humans). Holding this view, fishing can be seen as an energy recovery optimization problem.
A model therefore might lend insight into how tinkering with an ecosystem can provide the best results for humans. For example, it might be found that establishing hunting laws that specify minimum species levels could lead to an increase commercial profitability. These minimum levels are represent in the model with the critical level slider.
@#$#@#$#@
EditorDeRedes_0.2
@#$#@#$#@

@#$#@#$#@
Evacuation of a lecture hall
@#$#@#$#@
This model shows the evacuation of a room. In this case it is a lecture hall. Depending on the number of persons in the lecture hall and depending on a chance of hanging behind, the time to evacuate the whole lecture hall will decrease or increase.
@#$#@#$#@
sustainable forestry
@#$#@#$#@
This simulation shall proof that sustainability in forestry is more economic in a long term than non sustainable economy.
@#$#@#$#@
THC_final
@#$#@#$#@
This model is a simulation which should give a general idea about how the thermohaline circulation (THC) works. Water-particles with higher density sink to the bottom of the ocean which causes an undertow which drives the circulation. The intention is to show the effects of different climate scenarios on the thermohaline circulation.
@#$#@#$#@
Dissemination of Culture
@#$#@#$#@
This is a replication of Robert Axelrod's model of cultural dissemination, as presented in "The Dissemination of Culture: A Model with Local Convergence and Global Polarization".
@#$#@#$#@
WSN
@#$#@#$#@
This application is a simulation of data dissemination flooding technique in wireless sensor network. Such a network is used to detect and report certain events across an expanse of a remote area - e.g., a battlefield sensor network that detects and reports troop movements. The idea behind this network is that it can be deployed simply by scattering sensor units across the area, e.g. by dropping them out of an airplane; the sensors should automatically activate, self-configure as a wireless network with a mesh topology, and determine how to send communications packets toward a data collector (e.g., a satellite uplink.) Thus, one important feature of such a network is that collected data packets are always traveling toward the data collector, and the network can therefore be modeled as a directed graph (and every two connected nodes can be identified as "upstream" and "downstream.")
A primary challenge of such a network is that all of the sensors operate on a finite energy supply, in the form of a battery. (These batteries can be rechargeable, e.g. by embedded solar panels, but the sensors still have a finite maximum power store.) Any node that loses power drops out of the communications network, and may end up partitioning the network (severing the communications link from upstream sensors toward the data collector.) Thus, the maximum useful lifetime of the network, at worst case, is the mnimum lifetime of any sensor.
@#$#@#$#@
VacancyChains
@#$#@#$#@
Vacancy chains are a means of resource allocation alternative to markets or other forms of competition. Vacancy chains take place if the resource is sufficiently specific and the information sufficiently restricted for there being only one applicant to the resource. In fact, if there are two or more applicants a competition sets in, and eventually a market may arise in order to manage this competition.
Quite often, organizations restrict information and require specificity in order to allocate resources by means of vacancy chains. For instance, positions can be made very specific and information on available positions can be made hardly available so careers happen because the retirement of a high-ranked official triggers a chain of promotions among his subordinates. Another instance may be the way the most expensive and unique houses are allocated. Similarly, vacancy chains have been observed among hermit crabs lining up for occupying empty shells. Decentralized allocation of problems among robots can also be achieved by means of vacancy chains.
The vacancy chains model considers a set of positions ordered in strata. If a vacancy is produced, the corresponding position is occupied by agents from lower strata. Thus, vacancy chains propagate from upper to lower strata.
@#$#@#$#@
Santa Fe Ant Trail
@#$#@#$#@
This application is a simulation of the "Santa Fe Ant Trail" which is a standard problem in the areas of Genetic Programming and Grammatical Evolution. The objective of this problem is to find a computer program to control an Artificial Ant, so that it can find all 89 pieces of food located on the grid.
With this model, the user can do the following things: a. Write a set of actions (in the NetLogo programming language) and run them to observe the behaviour of the Artificial Ant. b. Simulate, verify, and investigate the Santa Fe Ant Trail solutions of other related programs (for example, some Genetic Programming and Grammatical Evolution software packages.
@#$#@#$#@
Queueing_Simulation_Discrete_Event
@#$#@#$#@
This is a simple queueing system model, with a single, unlimited queue and 1-10 homogeneous servers. Arrivals follow a Poisson process, and service times are exponentially distributed.
@#$#@#$#@
lang-evolution
@#$#@#$#@
This is a model of language evolution, where agents are human populations that possess a dialect. A dialect is modelled here as simply an ordered array of ones and zeros.
@#$#@#$#@
lang-evolution-2
@#$#@#$#@
This is a model of language evolution, where agents are human populations that possess a dialect. A dialect is modelled here as simply an ordered two array of ones and zeros. One of these arrays is the 'core' of the dialect; it is smaller but more important, and as such plays a greater role in determining mutual intelligibility as well as having a slower mutation rate.
@#$#@#$#@
plant-migration
@#$#@#$#@
The thread on this issue was sent by Sarah in NetLogo discussion.
Two species of plants, which attributes may differ in term of reproduction capacity, are distributed in archipelago. Reproduction capacity is elaborated as maturity, flowering probability, fecundity, seed traveling distance and mortality after flowering. Once a plant produces seeds, the seeds can travel at particular distance. When the seeds stranded in an island, they will grow. But if the seeds landed in the ocean, they will die. After flowering, a plant can die.
Implemented by Desi Suyamto, Bogor, Indonesia, 13.March.2010.
@#$#@#$#@
Trade
@#$#@#$#@
This model describes a economy using three types of resources: water, food and energy. Inside this economy, there is an artificial society with the following characteristics: (i) the turtles are of two types: female and male; (ii) these turtles have a limited life expectancy determined by the parameters LifeExpectancyMax (maximum life expectancy) and LifeExpectancyMin (minimum life expectancy); (iii) the patches Pxy are of three types: type 1 that stores a certain amount of water, type 2 that stores a certain amount of food and type 3 that stores a certain amount of energy. (iv) a male and female turtle can create a couple and a number of children; (v) the children can inherit the wealth of their parents; (vi) the basic needs of every turtle are 1 unit of water, 1 unit of food and 1 unit of energy per one year; (vii) if these basic needs are not fulfilled then the respective turtle dies; (viii) if a turtle has an amount of wealth in water, food, and energy that exceeds a certain limit determined by the parameter TurtleMinWealthToBuy then it starts to buy resources from the other turtles that have an amount of resources that exceeds the value of the parameter TurtleMinWealthToSell.
@#$#@#$#@
creditcrunch
@#$#@#$#@
I have decided to model the credit crunch from its early stages where the banks signed many irresponsible loans in order to boost its profits, through to where these loans defaulted, to where the bank's collapse because of the worsening economy and weakening of the pound. The dynamic model allows for many input scenarios where the culprits that caused the credit crunch can be identified and focussed on, to find solutions as to how the crisis could have been prevented, or indeed can be prevented from a specific moment onwards.
@#$#@#$#@
UFO
@#$#@#$#@

@#$#@#$#@
Rubicism2
@#$#@#$#@
The idea comes when my sons are addicted to rubic cubes puzzle. Using standard algorithm available in the internet, they can fix the scrambled 3x3x6 rubic cublets for about 1-2 minutes in average. Although it is still far away from the world record, but they already make me as the real loser at home!
Then, I am interested not only at the speed of fixing a scrambled rubic, but also at what I term as 'problem solving efficiency'. Thus, I challenge my sons. I scrambled the cubes for given number of rotations and ask them to fix in a very slow motion, so I could count the total number of rotations they make for fixing the cube.
When I scrambled the cube for less than 4 rotations, my sons can still fix it in the same number of rotations. Certainly they sometimes can fix in a number of rotations that is less than the scrambling number of rotations, when I did pair of rotations which cancelled the scrambling (e.g. I turned the front side of the cube in a clock-wise direction and then turn the same part in a counter-clock-wise direction).
But, when I did more than 4 scrambling rotations, their fixing number of rotations are always more than my scrambling number of rotations.
What I can learn from this simple game (from my sons precisely!) is that when equilibrium of a system is perturbed, human efficiency to fix the system would likely never approach 100%. Here, efficiency is measured as the cost of fixing the problem, relative to the cost of perturbation that causes the problem. And of course, when the system is very complex, composed by number of elements, where interdependency of some elements is relatively high, then problem-solving efficiency is just like a dream. Perhaps, this is the reason of Ulrich Beck in hypothesing his thesis about "risk society".
I am sure that this idea can be explored further with regards to some issues. For example, one of the efforts in mitigating global warming (i.e. REDD: Reducing Emissions from Deforestation and Degradation) put efficiency as one of the assessment indicators for the approach.
However, this NetLogo version of rubic is still a toy. The different form the real rubic is that here, you can notice the number of scrambling rotations and the number of fixing rotations. I use standard notations on the type of rubic rotations, adopted world wide. So, have fun with it and hope you find yourself as the most efficient problem solver.
@#$#@#$#@
Raster_rent_gap
@#$#@#$#@

@#$#@#$#@
Quantum Life I
@#$#@#$#@
This is a model of a Quantum Game of Life with path-dependent local quantum computation, exemplifying a Quantum Cellular Automaton.
@#$#@#$#@
Bacteria
@#$#@#$#@
This model is a simple illustration of bacteria growth in the body, and how white bloods and antibiotics can be used to fight the infection. It is aimed as a basic educational model, giving an abstracted visual representation of the scenario.
A general bacterium reproduces by cell division. The cells grow to a fixed size then, reproduce through binary fission, and creates two identical clone daughter cells, doubling in quantity over a given time step.
@#$#@#$#@
Rubik3d
@#$#@#$#@
It is the 3D version of standard 3x3x3 rubik. Implemented in NetLogo by Desi Ariyadhi Suyamto and Aryo Adhi Condro. Dedicated for rubik cubers.
@#$#@#$#@
ZimmermanArmsTradePrototypev5
@#$#@#$#@

@#$#@#$#@
cooperazione
@#$#@#$#@
This model is the implementation of the one presented by Cohen, Riolo e Axelrod in the article "The Role of Social Structure in the Maintenance of Cooperative Regimes".
@#$#@#$#@
cultura
@#$#@#$#@
This model is the implementation of the one presented by Axelrod in the article "The Dissemination of Culture: a Model with Local Convergence and Global Polarization".
@#$#@#$#@
differenziazione
@#$#@#$#@
This model is the implementation of the one presented by Noah Mark in the article "Beyond Individual Differences: Social Differentiation from First Principles".
@#$#@#$#@
innovazione
@#$#@#$#@
This model is an implementation of the model presented in the paper "Accelerating the Diffusion of Innovations Using Opinion Leaders" by Thomas Valente and Rebecca Davis.
@#$#@#$#@
MaterialSim Grain Growth
@#$#@#$#@
Most materials are not continuous arrangements of atoms, but rather composed of thousands or millions of microscopic crystals, known as grains. This model shows how the configuration and sizes of these grains change over time. Grain size is a very important characteristic for evaluating the mechanical properties of materials; it is exhaustively studied in metallurgy and materials science.
Usually this kind of study is made by careful analysis and comparison of pictures taken in microscopes, sometimes with the help of image analysis software. Recently, as the processing power of computers has increased, a new and promising approach has been made possible: computer simulation of grain growth. Anderson, Srolovitz et al. proposed the most widely known and employed theory for computer modeling and simulation of grain growth, using the Monte Carlo method. Instead of considering the grains as spheres, and being obliged to make numerous geometrical approximations, Anderson proposed that the computer would simulate the behavior of each individual atom in the system. Each atom would follow a very simple rule: it will always try to have, in its immediate neighborhood, as many atoms as possible with the same orientation as it.
This model is part of the MaterialSim (Blikstein & Wilensky, 2004) curricular package. To learn more about MaterialSim, see http://ccl.northwestern.edu/materialsim/.
@#$#@#$#@
Rhythm Simulator
@#$#@#$#@
@#$#@#$#@
One_Stock_Systems
@#$#@#$#@
A one-stock model of a thermostat/furnance/room system. Using the System Dynamics Modeler, this model captures the essential design and behaviour of a Viessmann gas furnance being used in the Bas-Rhin of Alsace in France during winter. All temperatures are in centigrade and initial values and ranges have been choosen for a typical winter season in this region of the world.
@#$#@#$#@
Helper
@#$#@#$#@
@#$#@#$#@
FinalProject
@#$#@#$#@
Choose your game mode, there are two - Elimination and Horde. Elimination - kill all the enemies on your screen.A lower score = better score Horde - Waves of enemies try to kill you, see how long you can survive. 2. Adjust the difficultySlider (this only applies to Elimination Mode). 3. Select any character, they don't have special properties and their size doesn't affect detection by enemies. 4. Press Z to Setup the world. 5. With your mouse inside the world*****, press X once, you will not need to press it again.
@#$#@#$#@
Automated weather warning system for Airports (AWWSA)
@#$#@#$#@
Automated weather warning system for Airports (AWWSA) To identify the requirement of where and when an aircraft can/cannot fly safely; from the weather point of view.
@#$#@#$#@
Vision Cone Example 2
@#$#@#$#@
This model shows how to provide turtles with a rudimentary sense of vision. This is a modification of the Vision Cone Example model in NetLogo Model's Library: Code Examples &gt; Vision Cone Example.
@#$#@#$#@
Vacuum Cleaner Robot
@#$#@#$#@
This model simulates a vacuum cleaner robot whose task is to clean the floor of a room
@#$#@#$#@
Two States
@#$#@#$#@
This model shows how to draw a simple two-state Finite State Automata (FSA) that represents turning a light switch off or on.
@#$#@#$#@
Sudoku Builder
@#$#@#$#@
This model allows the user to fill in a Sudoku puzzle.
@#$#@#$#@
Stick Figure Walking
@#$#@#$#@
This model provides a simple animation of a stick figure walking.
@#$#@#$#@
Stick Figure Animation
@#$#@#$#@
Users of this model can create their own stick figure animations and save them as QuickTime movie files.
@#$#@#$#@
State Machine Example 2
@#$#@#$#@
This model adds a function and plot to estimate and graph the self-organisation of the termites for the State Machine Example model in NetLogo Model's Library: Code Examples &gt; State Machine Example.
@#$#@#$#@
Simple Walk
@#$#@#$#@
This model gets a turtle to execute some simple walking commands.
@#$#@#$#@
Shuffle and Deal Cards
@#$#@#$#@
This model is an extension of the Shuffle Cards model that allows you to deal the cards as well.
@#$#@#$#@
Shuffle Cards
@#$#@#$#@
This model shows how you can create a pack of cards using turtle shapes and then shuffle them using the shuffle command.
@#$#@#$#@
Shannon Guessing Game
@#$#@#$#@
This model shows how a language model can be constructed from some training text and then used to predict text - i.e. play the "Shannon Guessing Game", a game where the agent (human or computer) tries to predict upcoming text, one letter at a time, based on the prior text it has already seen.
@#$#@#$#@
Searching Mazes
@#$#@#$#@
This model applies standard search algorithms to the problem of searching mazes.
@#$#@#$#@
Searching for Kevin Bacon 2
@#$#@#$#@
This model is an extension to the Searching for Kevin Bacon model that provides an Output that allows the user to trace how the search proceeds.
@#$#@#$#@
Searching for Kevin Bacon
@#$#@#$#@
This model applies standard search algorithms to the problem of searching for a specific goal node in a network.
@#$#@#$#@
Santa Fe Trail 2
@#$#@#$#@
This model tests out various behaviours as solutions to the Santa Fe Ant Trail problem. The Santa Fe Ant Trail was devised by John Koza in order to test the performance of evolutionary algorithms.
@#$#@#$#@
Obstacle Avoidance 2
@#$#@#$#@
This model is an attempt to recreate boids (see Craig Reynold's work) that employs basic obstacle avoidance steering behaviour.
@#$#@#$#@
Obstacle Avoidance 1
@#$#@#$#@
This model is an attempt to recreate boids (see Craig Reynold's work) that employs basic obstacle avoidance steering behaviour.
@#$#@#$#@
NZ Birds
@#$#@#$#@
This model constructs and animates a decision tree for the problem of identifying New Zealand birds.
@#$#@#$#@
Nested Triangles
@#$#@#$#@
This model shows how to use simple turtle drawing commands to draw some patterns made out of triangles.
@#$#@#$#@
Nested Squares
@#$#@#$#@
This model shows how to draw squares six different ways.
@#$#@#$#@
N Dimensional Space
@#$#@#$#@
This model visualises N dimensional data concerning New Zealand All Blacks.
@#$#@#$#@
Missionaries and Cannibals
@#$#@#$#@
This model applies standard search algorithms to the classic search problem called Missionaries and Cannibals.
@#$#@#$#@
Mazes-2
@#$#@#$#@
This extends the Mazes model by adding the Butterfly Maze, and two further behaviours based on those from the Searching Mazes model.
@#$#@#$#@
Mazes
@#$#@#$#@
This model shows how to get a simple reactive turtle agent to move around a maze.
@#$#@#$#@
Map Drawing
@#$#@#$#@
Users can create their own maps using this model.
@#$#@#$#@
Map and Image Annotator
@#$#@#$#@
Users can annotate maps and images using this NetLogo model.
@#$#@#$#@
Manhattan Distance
@#$#@#$#@
This model illustrates the concept of Manhattan distance, and compares it to Euclidean distance.
@#$#@#$#@
Look Ahead Example 2
@#$#@#$#@
This model shows how to provide turtles with a rudimentary sense analogous to the sense of vision. This is a modification of the Look Ahead Example model in NetLogo Model's Library: Code Examples &gt; Look Ahead Example.
@#$#@#$#@
Load File
@#$#@#$#@
This model shows how to load text from a file.
@#$#@#$#@
Line of Sight Example 2
@#$#@#$#@
This model shows how to provide turtles with a rudimentary sense of vision based on simulating a line of sight. This is a modification of the Line of Sight Example model in NetLogo Model's Library: Code Examples &gt; Line of Sight Example.
@#$#@#$#@
Life Example
@#$#@#$#@
This model shows how to use some simple commands in NetLogo to simulate the life cycle of people.
@#$#@#$#@
Life Cycle Stages
@#$#@#$#@
This model shows an example of a finite state automata (FSA) that represents the life cycle stages of people throughout their lives.
@#$#@#$#@
Language Modelling
@#$#@#$#@
This model shows how a language model can be constructed from some training text. Its purpose is to show various important features of language models and to visualise them using NetLogo link and turtle agents.
@#$#@#$#@
Knowledge Representation
@#$#@#$#@
This model visualises the knowledge and reasoning processes for three toy problems using different methods for knowledge representation.
@#$#@#$#@
Hill Climbing with Wall Following
@#$#@#$#@
This model implements turtle agents that can use a sense of what's up or down to perform hill climbing, or use a sense of touch via proximity detection to perform wall following, or can do both.
@#$#@#$#@
Hill Climbing Example 2
@#$#@#$#@
This model show how to give turtle agents a sense of what's up and what's down to perform hill climbing. This is a modification of the Hill Climbing model in NetLogo Model's Library: Code Examples &gt; Hill Climbing Example.
@#$#@#$#@
Hampton Court Maze with Wall Following
@#$#@#$#@
This model gets a turtle to wander around the Hampton Court maze using wall following behaviour.
@#$#@#$#@
Hampton Court Maze
@#$#@#$#@
This model draws a schematic representation of the Hampton Court Palace garden maze.
@#$#@#$#@
Foxes and Rabbits 2
@#$#@#$#@
This model creates foxes and rabbits. Once created, the rabbits move away from the foxes if they are too near.
@#$#@#$#@
Foxes and Rabbits
@#$#@#$#@
This NetLogo model creates 100 foxes and 1000 rabbits.
@#$#@#$#@
Communication T-T Example 2
@#$#@#$#@
This model simulates the spreading of a message between agents. This is a modification of the Communication T-T Example model in NetLogo's Models Library: Code Examples &gt; Communication T-T Example.
@#$#@#$#@
Follow Trail
@#$#@#$#@
This model allows the user to test out various trail following behaviours for ants. It is an extension of the Santa Fe Trail model.
@#$#@#$#@
Follow and Avoid
@#$#@#$#@
This model is an attempt to recreate boids (see Craig Reynold's work) that use seeking and fleeing steering behaviours.
@#$#@#$#@
Flocking with Obstacles
@#$#@#$#@
This model is an attempt to mimic the flocking of birds. It recreates boids (see Craig Reynold's work) that use various steering behaviours. This is a modification of the Flocking model in NetLogo Model's Library: Code Examples &gt; Flocking Example.
@#$#@#$#@
Firebreak
@#$#@#$#@
This model is an extension of the Fire model that allows users to add firebreaks, extra forest and ignition points. An satellite or aerial image can also be imported into the environment.
@#$#@#$#@
Entropy Calculator
@#$#@#$#@
This model allows the user to calculate the entropy for a specific probability distribution.
@#$#@#$#@
Empty Maze with Wall Following
@#$#@#$#@
This model gets a turtle to wander around the empty maze using wall following behaviour.
@#$#@#$#@
Empty Maze
@#$#@#$#@
This model draws an empty maze with no inside walls.
@#$#@#$#@
Crowd Path Following
@#$#@#$#@
This model is an attempt to recreate boids (see Craig Reynold's work) that use the crowd path following steering behaviour.
@#$#@#$#@
Colour Cylinder
@#$#@#$#@
This model demonstrates how colour can be represented in 3 dimensions: hue, saturation and brightness.
@#$#@#$#@
Chevening House Maze with Wall Following
@#$#@#$#@
This model gets a turtle to wander around the Chevening House maze using wall following behaviour.
@#$#@#$#@
Chevening House Maze with Coloured Islands
@#$#@#$#@
This NetLogo model colours the islands in the Chevening House garden maze.
@#$#@#$#@
Chevening House Maze
@#$#@#$#@
This model draws a schematic representation of the Chevening House garden maze.
@#$#@#$#@
Chatbot
@#$#@#$#@
This model implements two basic chatbots - Liza and Harry - using regular expressions (via an extension to NetLogo).
@#$#@#$#@
Central Park Events
@#$#@#$#@
This model visualises a sequence of events that are necessary for going from the Zoo to the Boat Pond in Central Park, New York.
@#$#@#$#@
Cars Guessing Game
@#$#@#$#@
This  model plays a simple game trying to guess the colour of cars as they drive past. Its purpose is to show how entropy and code length calculations are made given a probability distribution.
@#$#@#$#@
Being Kevin Bacon
@#$#@#$#@
This model implements various algorithms related to communication amongst agents in a network such as Dijkstra's algorithm, and communication via word-of-mouth or using blackboards. It also demonstrates some important concepts such as the small world phenomenon, degrees of separation, and super-nodes in peer to peer networks.
@#$#@#$#@
ANZ Continental Drift
@#$#@#$#@
This model shifts New Zealand back towards Australia in order to illustrate the process of continental drift. In effect, the model is running time backwards in order to show where New Zealand was in relation to Australia millions of years ago.
@#$#@#$#@
Agent Animation
@#$#@#$#@
This NetLogo model performs a simple animation of various turtle agent shapes to give the impression that they are flowing past the observer.
@#$#@#$#@
Wall Following Events
@#$#@#$#@
This model visualises a small set of events that an agent can follow in order to perform a modified type of wall following behaviour where sensing, thinking and acting are all done concurrently in no particular order (see the Wall Following Example 2 model for further exaplanation).
@#$#@#$#@
Wall Following Example 2
@#$#@#$#@
This model shows how to provide turtles with an ability to follow walls. This is a modification of the Wall Following Example model in NetLogo Model's Library: Code Examples &gt; Wall Following Example. The purpose is to show how to implement a "Sense &amp; Think &amp; Act" type behaviour where sensing, thinking and acting are done concurrently rather then a "Sense - Think - Act" type behaviour where sensing, thinking and acting are done one after the other.
@#$#@#$#@
Water Flowing Uphill
@#$#@#$#@
This model tries to visually simulate one possible solution to the problem of trying to get water to flow uphill.
@#$#@#$#@
TowerofHanoi
@#$#@#$#@
The Tower of Hanoi or Towers of Hanoi is a mathematical game or puzzle. It consists of three poles, and a number of disks of different sizes which can slide onto any poles. The puzzle starts with the disks in a stack in ascending order of size on pole A, the smallest at the top, thus making a conical shape. The objective of the puzzle is to move the entire stack to another pole according to the following rules: 1. Only one disk may be moved at a time. 2. Each move consists of taking the upper disk from one of the poles and sliding it onto another pole, on top of the other disks that may already be present on that pole. 3.No disk may be placed on top of a smaller disk.
@#$#@#$#@
17-Poker (FINAL)
@#$#@#$#@
17 Poker is simplifed version of one shot poker. By simplifed, I mean lazy.
@#$#@#$#@
CompExclusion
@#$#@#$#@
@#$#@#$#@
diffusion
@#$#@#$#@
This program first creates a social network and then simulates the diffusion of an innovation through the network following a combination of the Bass model and a network contagion model. Agents turn red as they adopt the innovation. New adopters are shown as hollow red circles and incumbent adopters as solid red circles. In a Bass model (unlike an S-I-R model) adoption is permanent. Small green numbers show the number of neighbors having adopted.
@#$#@#$#@
HabitatFragmentation
@#$#@#$#@
This model explores the stability of predator-prey ecosystems with fragmented habitats.
@#$#@#$#@
diffusion[1]
@#$#@#$#@
This is version 1.1 (8/19/2010) of this program. It is written in NetLogo 4.1.
@#$#@#$#@
Silence spiral
@#$#@#$#@
@#$#@#$#@
AntTaskAlloc
@#$#@#$#@
@#$#@#$#@
CASM_Robot
@#$#@#$#@
This program is simplified version of the one used for the work on Suhadolnik et al. (2010). If stock markets are complex, monetary policy and even financial regulation may be useless to prevent bubbles and crashes. On this study, we suggest the use of robot traders as an anti-bubble decoy. To make our case, we put forward a new stochastic cellular automata model that generates an emergent stock price dynamics as a result of the interaction between traders. After introducing socially integrated robot traders, the stock price dynamics can be controlled, so as to make the market more Gaussian.
We set the stochastic cellular automata model to study the stock price dynamics where the interactions between the market participants play a key role. Initially, there are only agent traders representing humans, and subsequently, robot traders enter the market. The traders are represented by cells on a two-dimensional L x L grid. There are N traders who can either buy or sell only one share, and these are two mutually exclusive states. At any given time step t, the population of traders N is divided into two distinct groups of buyers Nb and sellers Ns.
The stock market dynamics emerges as a result of the synchronous update of cells, according to a local probabilistic rule. Here, traders consider the information related to the behavior of their neighbors (Moore neighborhood) and also that related to the fundamentals. More details about the model can be found on Suhadolnik et al. (2010).
@#$#@#$#@
Silence spiral 2
@#$#@#$#@
This model is created by WANG Chengjun,who focused on the simulation of the spiral of silence theory which is very extensive grand theory.
@#$#@#$#@
Assignment
@#$#@#$#@
@#$#@#$#@
Terrorism_vs_Altruism
@#$#@#$#@
A simple model of cooperators (altruists/), cooperators who punish non-cooperators (police), non-cooperators who punish cooperators (terrorists/droogs), and non-cooperators who don't punish anybody.
@#$#@#$#@
ecosimple 
@#$#@#$#@
EcoSimple is an ecosystem model in which climate and interactive ecosystem processes dictate the relative abundance of biome types.
@#$#@#$#@
cyclic_cellular_automata
@#$#@#$#@
This is a cyclic cellular automata (CCA). CCA are caricatures of pattern formation in chemical oscillators and other exitable media.
@#$#@#$#@
Ants_AndrewE_add food3
@#$#@#$#@
This is an extention "Ants", a model included in the default model library of NetLogo. In this project, a colony of ants forages for food. Though each ant follows a set of simple rules, the colony as a whole acts in a sophisticated way.
@#$#@#$#@
leading according to needs
@#$#@#$#@
This model is used to test how leadership emerge from differences of nutrient requirements between group members. For a description of the model see: Sueur, C., Deneubourg, J.L., Petit, O., Couzin, I.D. 2010. Differences in nutrient requirements imply a non-linear emergence of leaders in animal groups. Plos Computational Biology 6(9): e1000917. doi:10.1371/journal.pcbi.1000917
Five files are needed to run the model: attributes.txt file is used to implement individual characteristics in the model. Row 1 corresponds to the identity of agents. Row 2 represents the body mass. Row 3 is the daily protein requirement. Row 4 is the daily energy requirement. Row 5 is the protein intake rate. Row 6 is the energy intake rate. Row 7 is the daily water requirement. Row 8 is the daily social time requirement. Row 9 is the daily resting time requirement. Row 10 is the category of individuals (male, female, etc.). Links.txt file is used to implement social relationships of individuals in the model. This variable is not used and analyzed in this study. activitybudget.doc file is used to score group activity budget per day. highestvalue.doc file is used to score which individual has the highest motivation at the end of the day and what is this motivation. idleaderfrequency.doc is used to score the frequency of leadership per individual during all the simulation.
@#$#@#$#@
fission
@#$#@#$#@
This models is used to understand how an animal group splits. Two files are needed: a link.txt for relationships between individuals and an attributes.txt. for individual characteristics. For more information see:
- Sueur, C., Petit, O. & Deneubourg, J.L. 2010. Short-term group fission processes in macaques: a social networking approach. Journal of Experimental Biology, 213, 1338-1346. doi:10.1242/jeb.039016
- independence vs. mimetism model: http://ccl.northwestern.edu/netlogo/models/community/Independence%20vs%20mimetism
@#$#@#$#@
Bandwagon 2D
@#$#@#$#@
This simple model reflects Granovetter's (1978) idea of how the bandwagon effect emerges. He takes a riot as an example of the phenomenon. Bandwagon is usually described as the tendency to adopt a technique, innovation, behavior, thought, process, or attitude because of its popularity or, that is the same, because that is what the sheer number of peers are doing. According to Granovetter, bandwagon emerges through the idea of a "threshold" level. This is, for the individual, "the proportion of the group he would have to see join before he would do so" (Granovetter 1978, p. 1422). He also specifies that the "threshold is simply that point where the perceived benefits to an individual of doing the thing in question [É] exceed the perceived costs" (p. 1422). Imagine 100 individuals and that "there is one individual with threshold 0, one with threshold 1, one with threshold 2, and so on up to the last individual with threshold 99. [...] The outcome is clear and could be described as a 'bandwagon' or 'domino' effect" (1424).
Default settings of the model (i.e., randomize = off) show a pattern of bandwagon diffusion (or effect) that reflect Granovetter's idea. If you switch 'randomize,' to the 'on' position, random thresholds are assigned to agents and the model significantly deviates from the standard Granovetter's. These "deviated" models are meant to be better approximations of what happens to real bandwagon phenomena.
@#$#@#$#@
Rhythm Simulator 2
@#$#@#$#@
This is a simulation of the electrical activity of the ventricles of the human heart. It incorporates a semi-realistic electrophysiologic model of the heart, and the impact that cardiac output has on the health of the rest of the human body.
@#$#@#$#@
Proyecto_Final Computacionales 2
@#$#@#$#@
@#$#@#$#@
David Miller - Resteraunt Model
@#$#@#$#@
This is a geospatial model of the dynamics within a sushi restaurant built in order to demonstrate several key notions related to complexity theory. It additionally analyses the multiple relationships between the different systems involved allowing the observer to find an optimal system for serving customers while keeping angry customer to a minimum. Though being less abstract than most this model could potentially be useful commercially in increasing restaurant efficiency it should mainly be seen as an educational aid as the simplifications make it unrealistic.
@#$#@#$#@
Artillery
@#$#@#$#@
This model is based on the classic game Tank Wars. Players must adjust angle and power of fire to hit a target with a projectile. Several factors, including gravity and wind must be taken into account.
@#$#@#$#@
HnH
@#$#@#$#@
This is an extremely simplified model of the influence of cultural or "memetic" trait transfer upon population dynamics, roughly corresponding to that first articulated in the book _Culture and the Evolutionary Process_ by Robert Boyd and Peter J. Richerson (1988), and put forward as a "paradigmatic example in memetics" by Derek Gatherer in the Journal of Memetics (2005). Rather than using an abstract recursive procedure involving the population proportions, however, this model uses individual interacting agents in a space. The spatial dynamics may be of interest: in particular, the formation of population source clusters under some conditions was a little surprising to me.
@#$#@#$#@
Plasmoknowlesim
@#$#@#$#@
This model is a simple illustration of the life-cycle of the parasitic protozoa "Plasmodium knowlesi", and how several strategies may help to control the disease (knowlesi' malaria). It has been devised as a basic visual model, giving an overview of the scenario where pathogen and hosts interact.
@#$#@#$#@
Leishmanisim
@#$#@#$#@
This model is a simple illustration of the life-cycle of the flagellate protozoa "Leishmania infantum" in Southern Europe, and how several strategies may help to control the disease (called "leishmanisosis"). It has been devised as a basic visual model, giving an overview of the scenario where pathogen and mammals interact.
@#$#@#$#@
Egranulosim
@#$#@#$#@
@#$#@#$#@
Cryptosporisim
@#$#@#$#@
This model is a simple illustration of the life-cycle of the parasitic protozoa "Cryptosporidium parvum", and how several strategies may help to control the disease (Cryptosporidiosis). It has been devised as a basic visual model, giving an overview of the scenario where pathogen and hosts interact.
@#$#@#$#@
Brugiasim
@#$#@#$#@
This model is a simple illustration of the life-cycle of a filarial parasitic nematode (called Brugia malayi), and how several strategies may help to control the disease. It has been devised as a basic visual model, giving an overview of the scenario where pathogen and hosts interact.
@#$#@#$#@
Babesim
@#$#@#$#@
This model is a simple illustration of the life-cycle of the parasitic protozoa "Babesia microti", and how several strategies may help to control the disease (babesiosis). It has been devised as a basic visual model, giving an overview of the scenario where pathogen and hosts interact.
@#$#@#$#@
Anisakisim
@#$#@#$#@
This model is a simple illustration of the life-cycle of the parasitic nematode "Anisakis simplex", and how several strategies may help to control the disease (anisakiosis or anisakidosis). It has been devised as a basic visual model, giving an overview of the scenario where pathogen and hosts interact.
@#$#@#$#@
Ants_AndrewE_add ans5
@#$#@#$#@
This is an extension of "Ants", a model included in the default model library of NetLogo. In this project, a colony of ants forages for food. Though each ant follows a set of simple rules, the colony as a whole acts in a sophisticated way.
@#$#@#$#@
Zombies 4.9
@#$#@#$#@
@#$#@#$#@
SegregationExpanded
@#$#@#$#@
This project models the behavior of two types of turtles in a mythical pond. The red turtles and green turtles get along with one another. But each turtle wants to make sure that it lives near some of "its own." That is, each red turtle wants to live near at least some red turtles, and each green turtle wants to live near at least some green turtles. The simulation shows how these individual preferences ripple through the pond, leading to large-scale patterns.
This project was inspired by Thomas Schelling's writings about social systems (such as housing patterns in cities).
@#$#@#$#@
Wave Interaction with Chladni Patterns
@#$#@#$#@
@#$#@#$#@
EXPLORE VS EXPOLTE
@#$#@#$#@
The Exploratron versus Exploitation Dilemma in Innovation
This Netlogo example is meant to accompany Garica (200x), "Uses of Agent-Based Modeling in Innovation/New Product Development Research", Jouranl of Product Innovation Management. This NetLogo Exploration/Exploitation agent-based model has been designed for the observation of how different resource allocation strategies can affect performance and market share in differing consumer markets and competitive environments. It has been proposed that the ecology of competition influences the degree of emphasis of firms on exploration and exploitation activities for producing new products - the greater the competition, the greater the need to exphasize exploration of new technologies (Brenner and Tushman 2003; Ghemawat and Costa 1993).
This model looks at the product development strategy made by innovative firms as they create new products for the marketplace. The makeup of the consumers (early adopters of new technologies vs. late adopters of new technologies) and the number of competitors selling similar products to these consumers will affect the firm's new product development strategies and their subdsequent successes in the marketplace.
See Garcia, Rummel & Calantone "The Exploratron versus Exploitation Dilemma in Innovation: A Complex Adaptive Systems Approach", working paper at http://igimresearch.cba.neu.edu/netlogo for details.
@#$#@#$#@
EXPLORE VS EXPOLTE1
@#$#@#$#@
The Exploratron versus Exploitation Dilemma in Innovation
This Netlogo example is meant to accompany Garica (200x), "Uses of Agent-Based Modeling in Innovation/New Product Development Research", Jouranl of Product Innovation Management. This NetLogo Exploration/Exploitation agent-based model has been designed for the observation of how different resource allocation strategies can affect performance and market share in differing consumer markets and competitive environments. It has been proposed that the ecology of competition influences the degree of emphasis of firms on exploration and exploitation activities for producing new products - the greater the competition, the greater the need to exphasize exploration of new technologies (Brenner and Tushman 2003; Ghemawat and Costa 1993).
This model looks at the product development strategy made by innovative firms as they create new products for the marketplace. The makeup of the consumers (early adopters of new technologies vs. late adopters of new technologies) and the number of competitors selling similar products to these consumers will affect the firm's new product development strategies and their subdsequent successes in the marketplace.
See Garcia, Rummel & Calantone "The Exploratron versus Exploitation Dilemma in Innovation: A Complex Adaptive Systems Approach", working paper at http://igimresearch.cba.neu.edu/netlogo for details.
@#$#@#$#@
totalistic2dCA
@#$#@#$#@
This is a totalistic 2 dimensional cellular automata explorer.
@#$#@#$#@
Neture
@#$#@#$#@
Neture is a NetLogo model that simulates how Nature works.Neture simulates a terrestrial ecosystem at the interface of ecology and evolution. The model embraces the three main ecosystem components: (1) the landscape environment, (2) the producers, and (3) the decomposers. It assembles processes that operate on a local spatial scale, endure decades, but progress with daily time steps.
@#$#@#$#@
1dCAexplorer
@#$#@#$#@
This is a 1 dimensional cellular automata explorer
@#$#@#$#@
Estimate the Value of Social-Capital
@#$#@#$#@
@#$#@#$#@
evolution_of_aggression
@#$#@#$#@
This model explores the evolution of aggresion in a system consisting of animals fighting for a resource necessary for reproduction. Three different strategies are considered: doves, hawks and retaliators.
1. Doves are not aggresive, they start displaying and retreat at once if their opponent is aggresive. When both opponents display one of them eventually gives up the reward to the other one but both pay a cost for wasting time.
2. Hawks are aggresive and fight with opponents that do not retreat until one of them is seriously injured and the other one gets the reward.
3. Retaliators start displaying but become aggresive when their opponents are aggresive. They behave as doves when confronted with a dove or another retaliator and as a hawk when they fight a hawk.
This project explores if any of the three strategies is an ESS (Evolutionary Stable Strategy), a strategy that when adopted by most of the individuals in the population cannot be invaded by another strategy.
@#$#@#$#@
gttrolley
@#$#@#$#@
@#$#@#$#@
Jill's Ants
@#$#@#$#@
This model models the movement of cars on a highway. Each car follows a simple set of rules: it slows down (decelerates) if it sees a car close ahead, and speeds up (accelerates) if it doesn't see a car ahead.
The model demonstrates how traffic jams can form even without any accidents, broken bridges, or overturned trucks. No "centralized cause" is needed for a traffic jam to form.
@#$#@#$#@
Light bike
@#$#@#$#@
This is a reproduction of the Light Bikes from Tron. Being a two player game, there are two players, a red player and a blue player. They lay down a colored trail, and when they run in to a trail, their own, or the other player's, they will crash.
@#$#@#$#@
tank
@#$#@#$#@
@#$#@#$#@
psychotest
@#$#@#$#@
Psychotest.
Simuluje reálný psychotest, jen msto zvuku je použita zmìna pozad na žlutou a msto pedálù klávesy A a S.
Vytvoøil Ondøej Èerný
Simulates a real psychotest, but the sound is here simulate by changing background-color yellow and pedals are simulated by keys A & S
Made by Ondøej Èerný
@#$#@#$#@
bucketsort
@#$#@#$#@
About Bucket Sort:
Bucket Sort is not really a sorting algorithm, it is a process to improve sorting efficiency.Usually used in conjunction with another sorting algorithm. But it can be used alone.
@#$#@#$#@
maze game
@#$#@#$#@
@#$#@#$#@
game
@#$#@#$#@
@#$#@#$#@
Wikimodel
@#$#@#$#@
Wikis are collaborative platforms for text creation. The original idea of hypertext, expressed by V.Bush, D.Engelbart and T.Bernes-Lee treated it as an extension not only of individual, but of collective capabilities. Wiki is a simple and radical instance of a collective hypertext, in which every community member can create and edit pages. Wikis are often referred to as tools for conducting collective activities. Wiki philosophy implies aiming the efforts of the whole group at creating a collective final product. A group of wiki users can elaborate a collective hypertext and not bother with maintaining links. Usually wikis are regarded as encyclopedias consisting of multiple interconnected entries or as a multi-agent network community. In this paper we refer to wikis as ecological systems which consist of multiple human and programmed agents, following certain rules and an environment of various objects, pages, templates and categories and links between them. All the elements of the wiki environments can be reused. The transclusion mechanism allows to use wikis as building blocks and construct complicated metabolic chains. Well known wiki examples are collections of entries created by the community and are indicative examples of ecological systems.
@#$#@#$#@
Ghostly
@#$#@#$#@
Turtles with pen down follow the mouse. They all have different x and y velocity reducing multipliers.
@#$#@#$#@
flame
@#$#@#$#@
This is something that is intended to look like a flame. Heat diffuses and evaporates in the world. Invisible particles produce heat and cool down with various speed (faster if heat > ideal-heat, slower otherwise). New particles are created at the bottom of the world with random positions and output-heats. Particles move to the best closest patch from the 3 closest next patches in the next row. Best patch is the patch with least absolute value of the particles ideal temperature - heat. All particles have the same ideal-heat which is 15
@#$#@#$#@
WealthDistribRes
@#$#@#$#@
This model WealthDistribRes can be used to study the distribution of wealth in function of using a combination of resources classified in two renewable and nonrenewable. This agent-based computational model created in NetLogo 4.0.5 has the following fundamental characteristics: (i) the turtles are of two types: female and male; (ii) these turtles have a limited life expectancy determined by the parameters LifeExpectancyMax (maximum life expectancy) and LifeExpectancyMin (minimum life expectancy); (iii) patches stores a certain amount of water ResWater?0, a certain amount of food ResFood?0, a certain amount of coal ResCoal?0, a certain amount of oil ResOil?0, a certain amount of gas ResGas?0, a certain amount of uranium ResUranium?0, a certain amount of wind ResWind?0, a certain amount of sun ResSun?0, a certain amount of tides ResTides ?0, and a certain amount of geothermal heat ResGeothermalHeat?0; all these resources are converted in energy; these ten resources are divided in two: the first type are renewable resources and here are included water, food, wind, geothermal heat, tides and sun resources that are replenished on every simulation step; the second type are nonrenewable resources (coal, oil, gas, uranium); (iv) a male and female turtle can create a couple, and a number of children; (v) the children can inherit the wealth of their parents; (vi) the needs of every turtle are 1 of energy per one year processed from the available resources found on the patches; (vii) if these basic needs are not fulfilled then the respective turtle dies.
@#$#@#$#@
BIGmodel
@#$#@#$#@
@#$#@#$#@
agentworld
@#$#@#$#@
Agents in a world with various interaction rules. Different rules produce different behaviour. This model is very similar to Heatbugs and Slime which can be found in netlogo models library.
@#$#@#$#@
MCLOUD-1
@#$#@#$#@
MCLOUD-1 ( Mathematical Cloud one-layer network) is a minimal, one-layer stochastic CA network model of the Arctic bromine explosion (Arctic BE).
Sketchily, Arctic BE can be characterized by the time-varying total amount BrO and its lifetime. We construct a flow distribution network with a predefined output pattern of the total amount BrO (the satellite BrO samples).
We assume that the predefined output pattern is a distribution made up of the countable number of the mass points < nodes of the abstract network>. From a deeper perspective, the total amount BrO is a distribution over distributions.
We build a minimal network which describes relations of the mass BrO distribution and distribution of the adaptive aerosol loading. Even the minimal solution becomes far from trivial because of the uncertainties in aerosol loads and the lack of data concerning decline phase of Arctic BE.
@#$#@#$#@
Model 31-03-2011
@#$#@#$#@
This project models the flow of traffic around a familiar 'diversion' scenario. Each car follows a simple set of rules: - Adhere to the speed limit - If car ahead is stopped, stop. - If road ahead is closed, find available route. - If light is red, stop. - If light is green, go.
The model is used to demonstrate how small adjustments in the world can affect traffic flow, including phasing of traffic lights, acceleration/deceleration variables and road closures.
@#$#@#$#@
Gestion de migration 25mars11
@#$#@#$#@
@#$#@#$#@
19Mai11
@#$#@#$#@
Simulation d'embarquement des conteneurs sur un port
@#$#@#$#@
3Economies
@#$#@#$#@
This agent-based computational model created in NetLogo 4.0.5 and can be used to study the relation between wealth distribution measured by Gini index and technological progress. It has the following fundamental characteristics: (i) the turtles are of two types: female and male; (ii) these turtles have a limited life expectancy determined by the parameters LifeExpectancyMax (maximum life expectancy) and LifeExpectancyMin (minimum life expectancy); (iii) patches stores a certain amount of water ResWater>=0, a certain amount of food ResFood>=0, a certain amount of coal ResCoal>=0, a certain amount of oil ResOil>=0, a certain amount of gas ResGas>=0, a certain amount of uranium ResUranium>=0, a certain amount of wind ResWind>=0, a certain amount of sun ResSun>=0, a certain amount of tides ResTides>=0, and a certain amount of gethermal heat ResGeothermalHeat>=0; all these resources are converted in energy; these ten resources are divided in two: the first type are renewable resources and here are included water, food, wind, geothermal heat, tides and sun resources that are replenished on every simulation step; the second type are nonrenewable resources (coal, oil, gas, uranium); (iv) a male and female turtle can create a couple, and a number of children; (v) the children can inherit the wealth of their parents; (vi) the needs of every turtle are 1 of energy per one year processed from the available resources found on the patches; (vii) if these basic needs are not fulfilled then the respective turtle dies.
@#$#@#$#@
Diabetes1
@#$#@#$#@
Diabetes and glucose simulation
@#$#@#$#@
Diabetes
@#$#@#$#@
Simulacion del cuerpo humano; piernas y torso.
Este sistema trata de simular el sistema endocrino de como interactua la glucosa, como el cuerpo la consume, asi como que sucede cuando ingerimos una dosis alta de carbohidratos; asi como el efecto del ejercicio en el consumo y reduccion de la glucosa en la sangre.
Es importante en este modelo observar que las mediciones de glucosa (cuadros de colores) tienen diferentes valores y se debe en algunos casos a el RETRASO en el tiempo debido a ladistancia que debe recorrer la glucosa (E insulina) asi como la señal de su consumo y vemos que esta asimetria y/o no linealidad del sistema nos permite hacer diseño de experimentos de forma rapida y efectiva.
@#$#@#$#@
Agent-based N-person prisoner's dilemma
@#$#@#$#@
Evolving N-Person Prisoner's Dilemma
@#$#@#$#@
circle
@#$#@#$#@
Example how to explain circle and ellipse basics
@#$#@#$#@
nn-inspiredCA
@#$#@#$#@

@#$#@#$#@
CSS Generator
@#$#@#$#@
wip pretty much
@#$#@#$#@
MattnKim
@#$#@#$#@

@#$#@#$#@
Modified random clusters method for landscape pattern simulation
@#$#@#$#@
A implementation of the modified random clusters method for landscape pattern simulation by Saura and Martinez-Millan (2000, http://dx.doi.org/10.1023/A:1008107902848) and implemented in SIMMAP. Used previously in Millington et al. (2008, http://jasss.soc.surrey.ac.uk/11/4/4.html).
@#$#@#$#@
moranforagers
@#$#@#$#@
This model investigates the evolutionary success of mutant foragers that have a selective advantage/disadvantage compared to indigenous foragers.
@#$#@#$#@
METAMORFOSIS
@#$#@#$#@
This program illustrates the cycles of metamorphosis of frogs.
@#$#@#$#@
Segundo jogo do conhecimento 2
@#$#@#$#@
This is the game of knowledge, that demonstrates knowledge of the culture of a company, in which six players interact. Based on: http://www.iterated-prisoners-dilemma.net/
I would advise to decrease the speed to see interactions better.
it's in portuguese, but google translate
helped by Ant™nio Carlos Barroso
@#$#@#$#@
PERSECUTIONS
@#$#@#$#@
A game of persecutions obsessives.
@#$#@#$#@
Feldman NetLogo Interface Algorithmic Finance
@#$#@#$#@
This is the basic version of a NetLogo model for financial markets.
@#$#@#$#@
Classic Traveling Salesman
@#$#@#$#@
This model solves the traveling salesman problem (a classic NP-hard problem) by means of a genetic algorithm. The model also incorporates the ERX crossover; a method of crossover specially developed for problems like the TSP. However, the code behind the algorithm is rather lengthy.
@#$#@#$#@
merchant
@#$#@#$#@
This is an economic model of banks, merchants, and shoppers, and how they interact and evolve, given only a few starting parameters.
@#$#@#$#@
finalfin
@#$#@#$#@
This model is my independent study for my Computer science bachelor's degree. The topic of this model is "Robots Cluster Model with Infrared by Clustering Algorithm" represented Infrared by color of turtle.
@#$#@#$#@
game
@#$#@#$#@
This is a bullet hell game. 
@#$#@#$#@
Solar Field Mapping 1p03
@#$#@#$#@
This "Solar Field Mapping" model mimics the motions of "large-scale" solar magnetic field lines on the Sun's surface. Solar magnetic field motions are complex and poorly understood. Yet we know they give rise to the solar dynamo, hence sunspots, flares, the Earth's Aurora, and other exotic terrestrial effects known as Space Weather. Space weather can affect satellites and power grids at times if a large specific event occurs. The photospheric field patterns in this model display the oscillating behavior of the Sun's "Dynamo," called that since it generates magnetic fields in "active regions" very much like a power plant generates electricity. The model displays other observed solar patterns,
and the model# is written as 1p03 meaning 1.03 .
@#$#@#$#@
Post-earthquake activity
@#$#@#$#@
This models simulates humans and traffic right after a given earthquake
@#$#@#$#@
The knowledge game
@#$#@#$#@
This is a translation of the "Segundo jogo do conhecimento 2." 

This is the game of knowledge, that demonstrates knowledge of the culture of a company, in which six players interact. Based on prisoners«dilemma.
@#$#@#$#@
Prisoner's dilemma by claudio
@#$#@#$#@
This is the prisoner's dilemma with up to six players and eight strategies.
@#$#@#$#@
FriendshipGameRev_1_0_25
@#$#@#$#@
This is a friendship game model. A friendship game is a kind of network game: a game theory model on a network. A game starts with a model of a network of turtles. Each turtle considers as its friends every other turtle that is linked directly on the network. Each turtle decides what strategy to play, x or y, based on the choices made by its friends. How the friends influence the choice depends on whether the game is one of strategic substitutes or strategic complements.
@#$#@#$#@
Haystacks
@#$#@#$#@
Implementation of John Maynard Smith's 'haystacks' model. This model demonstrates the way in which altruism in an isolated population can result in that population growing sufficiently fast in comparison to selfish populations that altruism predominates once the populations mix. Also includes preferential mixing (assortativity) which increases the effect by allowing altruists to mix primarily with other altruists.
@#$#@#$#@
Gravity (Final) - Ivaylo M
@#$#@#$#@
This is a planetary gravity simulator, or an orbital simulator. It simulates the orbits
of stellar bodies around each other depending on factors such as mass, speed, and distance. It also simulates collision between bodies. 
@#$#@#$#@
Agent-Based Model
@#$#@#$#@
Health care improvement efforts often focus on changing the behavior of individuals while the interdependencies among individuals are overlooked. The application of complex adaptive systems approach to studying healthcare delivery changes the focus of improvement efforts from the individual to the relationships and interdependencies among individuals in the system. Sensemaking and improvising are social activities that take place in the context of relationships between individuals. We explore the impact of sensemaking and improvising on patient outcomes in healthcare settings.
@#$#@#$#@
Copiar en los examenes
@#$#@#$#@
During the tests or examinations of the courses, some students try to copy each other. The teacher should prevent such fraud.
La copia en los examenes es, por desgracias, una tecnica bastante habitual. Lo que se presenta es un posible modelo de dicho fenomeno, con la actuacion del profesor para impedirlo.
@#$#@#$#@
Center of Mass v3
@#$#@#$#@
This model is designed to allow students to explore how they think about Center of Mass.
@#$#@#$#@
SolarSystemEnd
@#$#@#$#@
Death of Our Solar System
@#$#@#$#@
Flocking with Predator
@#$#@#$#@
A model which builds on the Flocking Model by Uri Wilensky by adding a predator adversary.
@#$#@#$#@
Steve Keens Endogenous Money Model (Agent-based implementation)
@#$#@#$#@
An attempt at implementing an agent-based version of Steve Keen's model of the monetary circuit (as described in 'Explaining profit with a dynamic model of the Circuit' by Steve Keen). The original model is a systems dynamics one.
@#$#@#$#@
trytodrawsolution
@#$#@#$#@
The incomplete Sudoku solution creation
@#$#@#$#@
Solar Field Mapping 1p07
@#$#@#$#@
This "Solar Field Mapping" model mimics the motions of "large-scale" solar magnetic field lines on the Sun's surface. Solar magnetic field motions are complex and poorly understood. Yet we know they give rise to the solar dynamo, hence sunspots, flares, the Earth's Aurora, and other exotic terrestrial effects known as Space Weather. Space weather can affect satellites and power grids at times if a large specific event occurs. The photospheric field patterns in this model display the oscillating behavior of the Sun's "Dynamo," called that since it generates magnetic fields in "active regions" very much like a power plant generates electricity. The model displays other observed solar patterns, and the model# is written as 1p07 meaning 1.07 .
@#$#@#$#@
Kanban3_v5
@#$#@#$#@
Kanban Simulation
@#$#@#$#@
Groupintegration_nobreededlinks
@#$#@#$#@
Test upload of a class simulation.
@#$#@#$#@
Bird's Eye
@#$#@#$#@
This model is based on Eagle's eye game by Lumosity. The object of the game is to recall the number flashed at the center of the screen and to point exact destination of the mother bird, which is indicated in red dot.

Both the number and bird's destination will be shown for a few seconds, so you have to focus on the screen when playing this game. The score is based on your performance, it may increase or decrease in the duration of the game.
@#$#@#$#@
Hemangioblast Determination
@#$#@#$#@
This is a heuristic model of mouse hemangioblast maturation at embryonic headfold stages.
@#$#@#$#@
TraitScape
@#$#@#$#@
This program allows an investigator to test hypotheses concerning the effect of three species traits (dispersal distance, reproductive rate, and movement behavior) on abundance within a focal area. The output includes information about habitat cover in 10 concentric rings and abundance of individuals in the focal area. These data can be used to calculate the scale of effect, or the distance from the center of a focal area at which habitat cover is most associated with abundance in the focal area.
@#$#@#$#@
Improved Clonal Selection Algorithm for Solving Travelling Salesman Problem (v_4_1_3)
@#$#@#$#@
Although many meta-heuristic algorithms were developed for solving combinatorial optimization problems, very few of them were realized in an agent based environment. The algorithms which model dynamics of Artificial Immune Systems (AIS) are population based approaches with adaptability characteristics, therefore AIS can be better realized in an agent based modeling environment. For this purpose first time in the literature a clonal selection algorithm which is an AIS based algorithm is modeled in a multi agent environment for solving the travelling salesmen problem which is a NP-hard combinatorial optimization problem. In order to observe the behavior of the algorithm simulation experiments are carried out on several test problems in NetLogo. Moreover, receptor change process and crossover mechanisms are integrated into the proposed model in order to improve the performance of the classical clonal selection algorithm. It is shown that there is a high potential to obtain good
 solution by making use of agent oriented approaches which can more realistically model the natural phenomenon.
@#$#@#$#@
Diffusion3
@#$#@#$#@
This model looks at social strengthening, a hypothesis of how religious ritual behaviors can facilitate cumulative cultural evolution in humans.
@#$#@#$#@
SpeciesWorld
@#$#@#$#@
Derived from the Daisy World idea, SpeciesWorld is a representation of an environment that can evolve feedback loops to maintain conditions to be suitable for life.
@#$#@#$#@
PARASITERMINATOR_1
@#$#@#$#@
Model in Spanish.
Parasiterminator 1 es un modelo grafico que ayuda a practicar de forma virtual el diagnostico diferencial y el tratamiento (en humanos) de 17 zoonosis parasitarias TROPICALES de interes medico y veterinario. Como el titulo del juego indica, el objetivo del jugador es diagnosticar eliminar mediante tratamiento a los parasitos que infectan a un grupo de humanos.
Para jugar con el programa necesita tener un conocimiento previo de los parasitos, asi como de su diagnostico y tratamiento.
AVISO IMPORTANTE: Este programa educativo es una simple herramienta docente y en ningun caso puede sustituir la consulta con personal sanitario profesional en caso de enfermedad.
@#$#@#$#@
PARASITERMINATOR_2
@#$#@#$#@
Model in Spanish.
Parasiterminator2 es un modelo grafico que ayuda a practicar de forma virtual el diagnostico diferencial y el tratamiento (en humanos) de 19 zoonosis parasitarias (muchas de ellas en zonas templadas) de interes medico y veterinario. Como el titulo del juego indica, el objetivo del jugador es terminar con los parasitos que infectan a un grupo de humanos.
Para jugar con el programa necesita tener un conocimiento previo de los parasitos, asi como de su diagnostico y tratamiento.
AVISO IMPORTANTE: Este programa educativo es una simple herramienta docente y en ningun caso puede sustituir la consulta con personal sanitario profesional en caso de enfermedad.
@#$#@#$#@
hydrogeol
@#$#@#$#@
This model computes :
- 2D underground flows through a porous aquifer
- 2D transfert of pollutant under a well influence
@#$#@#$#@
bc
@#$#@#$#@
This model demonstrates continuous opinion dynamics under bounded confidence, which treats models of some highly cited papers (see Info tab).
@#$#@#$#@
land-random
@#$#@#$#@
Freedom, in Biblical economy, means that every citizen owns a land-plot. Originally, this was achieved by two means:

 * Initially, all land was divided into equal plots, and each citizen got a plot;
 * Once in 50 years, in the year of Jubilee, all lands returned to the original owners.

This model checks whether it is possible to achieve the goal of Freedom (meaning, every citizen owns a land) even when the initial division is not equal.
@#$#@#$#@
land-income
@#$#@#$#@
This is an elaboration of the land-random model (http://ccl.northwestern.edu/netlogo/models/community/land-random), that takes differences in income into account.

Citizens gain income from several sources - some depend on land while others do not. Citizens buy land with probability that is directly proportional to their wealth - the rich are more probable to buy land than the poor. Can the Jubilee still help the poor get some land?
@#$#@#$#@
at
@#$#@#$#@
The following represents a model of Indo-Pakistani trade and how it is affected by conflict and cooperation.
@#$#@#$#@
parkingmodel
@#$#@#$#@
The aim of the model is to simulate cars who park in a street.
The cars may not park on parking space which are occupied by another car.
The cars prefer a parking space which isn't surrounded by another car.
@#$#@#$#@
abm art
@#$#@#$#@
This model generates ABM art.
@#$#@#$#@
TaskAllocation
@#$#@#$#@
This is an extension to the garbage can model in which tasks are allocated to workers (or teams of workers) according to different rules for matching workers' skills with the skills requested to perform the tasks.
@#$#@#$#@
Kiri test 2
@#$#@#$#@
This model demonstrates the pairing of guanine.
@#$#@#$#@
UMNdensity-fidelity
@#$#@#$#@
This model is a simulation of ant colony behavior. It allows the user to modify all aspects of the colony and compare it to an optimized ant colony. It measures collection rate and can modify the food distribution in the area through the use of sliders.
@#$#@#$#@
Finalproj
@#$#@#$#@
My project is a game called Logorunner. It is an imitation of Linerunner, the IOS game.
@#$#@#$#@
game1
@#$#@#$#@
This is a bullet hell game.
@#$#@#$#@
left-right-game
@#$#@#$#@
This is a simple game aimed at helping children learn their left and right. This version has sound.
@#$#@#$#@
left-right-game-no-audio
@#$#@#$#@
This is a simple game aimed at helping children learn their left and right. This version does not have sound.
@#$#@#$#@
value-iteration
@#$#@#$#@
The program compares deterministic and non-deterministic agents in goal seeking via reinforcement learning.
@#$#@#$#@
FlockingColor_v5
@#$#@#$#@
Color Flocking Model with Group-size calculation and direction output.
@#$#@#$#@
ClimateWise1.1
@#$#@#$#@
This model is inspired by Tom Seeley's work on the decision-making system of honeybees. It explores how decision-making systems and science dissemination impact climate change.
@#$#@#$#@
HOTnet
@#$#@#$#@
The model generates power-law networks by a process of Highly/Heuristically Optimized/Organized Tolerance/Tradeoffs, in which new network members make a connection to the members which optimize multiple functional objectives.
@#$#@#$#@
GBLCSA
@#$#@#$#@

<br><b>To use this model in its full form, please follow <a href="https://sites.google.com/site/jkgeconoeng/GBLCSA.zip">this link</a>.</b><br><br>

This model implements a genetic-based classifier system to forecast stock returns. It was developed in Galimberti and da Silva (2012) in order to provide an empirical assessment on the use of computationally intensive algorithms as representative of agent's process of inductive expectations formation. As such, it is not exactly a simulation model. Instead, it is an input-driven algorithm given that it requires a file with data on prices and other fundamental indicators in order to work.
@#$#@#$#@
VisualizationCommunities
@#$#@#$#@
This is a demonstration of the utility of network visualization and in particular spring layout algorithms.
@#$#@#$#@
Frogger Simple Reflect Agent
@#$#@#$#@
This is application of Simple Reflect Agent. This is my homework for the 5 th semester in Jurusan Teknik Informatika UIN Maulana Malik Ibrahim Malang Indonesia. http://uin-malang.ac.id/ this is one the real frog in middle with white color. other frog is sensor. frog around the white frog simulating when the real frog(white) at the same place. is life or dead ? if life frog can move there. if dead frog can move there and find other place that save. it simulate a Simple Reflect Agent move to the save place. I know this is far from perfect. but it nice to play with NetLogo. I hope we can discus it :-) http://tarecha.wordpress.com/ http://facebook.com/tarecha agung.tarecha@gmail.com Best Regards,
Mochamad Agung Tarecha, Malang, Indonesia. FYI : My other friend also have a same task, but with different algorithm, different game, different way...I hope they also share their idea.
@#$#@#$#@
Party Segregation
@#$#@#$#@
This is a modified version of 'Party' in the Models Library.  It is a model of a cocktail party, where men and women at the party form groups.  The party-goers have a TOLERANCE that defines their comfort level with a group that has members of the opposite sex.  If they are in a group that has a higher percentage of people of the opposite sex than their TOLERANCE allows, then they are considered "uncomfortable", and they leave that group to find another group.  Movement continues until everyone at the party is "comfortable" with their group.
@#$#@#$#@
Evil Bunny Bully Model
@#$#@#$#@
Bullying model that seems to have promise, but I'm not really finding a way to put it to practical use. An evil bunny basically terrorizes students - not exactly what I intended, but it was fun. This model is my first attempt at coding NetLogo, which it should be apparent that I liberally borrowed lines from every code I came across, including wolf-predation and zombie models, as well as the example codes and the manual. Feel free to send me feedback, as I'm sure there's a lot I did wrong and there are a great many users out there that can make netlogo sing.
@#$#@#$#@
Fall-of-banks
@#$#@#$#@
With this model you create a random economy, you can modify the intensity of relations between banks (the inversions, debts, etc.. that banks shares between them) and the size of all banks and the bank who star the crises. You can apply two solutions, made a "bail in" (changing debt for stock shares) or let the bank to crash and disappear. Is modificable the "bank panic" and the recovery chance of one bank or company in crises to return to normal status. There are two type of "turtles", banks and companies, the seconds could be destroyed if the banks get in crises (less loans to the companies), to simulate a complex economy, not only the financial system.
@#$#@#$#@
Fashion-Models
@#$#@#$#@
This is a simulation for a class project on agent-based modelling, in Nanyang Technological University (Singapore).

This model hopes to determine the aftereffects when fashion models (or any other influential agent) loses influence on individuals.

The description for the model is under the info tab in the model.

Do let me know of any feedback you may have concerning this model.
@#$#@#$#@
Smoking motivation peer pressure
@#$#@#$#@
The model displays differences in smoking behaviour as determined by peer pressure and motivational-orientation: whether an agent seeks approval from peers (extrinsically motivated) or from within himself (intrinsically motivated) influences their perception of and reaction to peer pressure.
@#$#@#$#@
PD N-Person with Strategies
@#$#@#$#@
This model aims to study the effects of cooperating and competing within a society; competitors gain more individually, while cooperators help the society to gain more collectively. Based on the Prisoner's Dilemma or Game Theory. The multi-person Prisoner's Dilemma considers a situation when each of N participants has a choice between two actions: cooperating with each other for the "common good" or defecting (following their selfish short-term interests). As a result of their choice, each participant receives a reward or punishment (payoff) that is dependent on its choice as well as everybody else's.
@#$#@#$#@
Occupational Stress Support
@#$#@#$#@
Model of occupational stress and agents' supportive or disruptive behaviors in an organizational setting. The model looks at how the agents influence each other to change their behaviors, and how occupational stress interact with neighboring agents' overall support to determine agents' job satisfaction.
@#$#@#$#@
Talk of Network
@#$#@#$#@
This model is built based on a journal article by Goldenberg et al. (2001) titled "Talk of the Network: A Complex Systems Look at the Underlying Process of Word-of-Mouth". This model is basically trying to mimic the spread of information through word-of-mouth. How a simple advertisement seen by only a few people can be effectively spread among the community members.
@#$#@#$#@
Positive & Negative Talk of Network
@#$#@#$#@
In brief, this simulation is built on as a continuation to the previous model on Talk of the Network (Goldenberg et al., 2001) with an add-on feature. As a add-on feature, current simulation will also be observing the effect of different valance of the information (e.g. positive or negative) towards the rate and end-result of the spreading of information. Moreover, according to the result collected by Deitz and Cakim (2005), the number of negative w-o-m overpower positive w-o-m by 1.133 times. The add-on feature in this simulation is based on a journal article titled "On Braggarts and Gossips: A Self-Enhancement Account of Word-of-Mouth Generation and Transmission" by Angelis, M.D. et al. (2012).
@#$#@#$#@
Immigrant, Leadership and Social change
@#$#@#$#@
Immigrant studies have become a popular psychosocial area to study and their impact to the current society is one of the topics.There are studies about segregation, especially in those societies with immigrants. While social influence is a model to understand how individuals could influence each other through dynamic interactions. Instead of solely looking at segregation or social influence seperately, this model is built to examine the pattern of social change by assuming the social segregation and influence occur at the same time. It's designed to examine the quantity, quality of immigrants and impacts caused to the society. The attitudes toward in-group and out-group, the proportion of immigrants, the quality of immigrants (leader-like characteristics which represent the degree of individual's influencial ability) are the variables used in this model. Different values of these variables could cause the social pattern changes in different manner.
@#$#@#$#@
The Influence of Obesity in a Social Network
@#$#@#$#@
This model looks at the spread of obesity (weight) in a social network, specifically amongst family and close friends. Many studies have supported this finding, linking obesity to circle of friends. It works on the the theory of homophily, where individuals often have the tendency to associate and adapt to similar others.
@#$#@#$#@
Pathological Gambling and Social Influence
@#$#@#$#@
this models simulates the gambling behavior of pathological gamblers under the influence of other pathological gamblers and ex-gamblers.
@#$#@#$#@
advanced enzyme kinetics
@#$#@#$#@
This model demonstrates the kinetics of single-substrate enzyme-catalysis. In Michaelis-Menten kinetics, there is typically a fixed initial substrate concentration. This is a limited model of biology. Enzymes in situ often work under rhythmic substrate input. Therefore, this model has the option to activate and modify a sigmoidal input of substrate.
@#$#@#$#@
Smoker Behavior and Intimacy
@#$#@#$#@
The model aims to look at the pattern of how the number of smokers or non-smokers can affect a smoker's behavior. In addition, the model aims to see how the strength of intimacy between the smoker and his surrounding people can affect his smoking behavior.
@#$#@#$#@
Facebook share on group buying decision
@#$#@#$#@
This model aims to find out how the positive effects of electronic word of mouth (eWOM) in influencing online buying behaviour using Facebook as an interactive platform.
@#$#@#$#@
Yawn Contagion
@#$#@#$#@
This model demonstrates a world where people live to yawn all their lives. 
@#$#@#$#@
Girls Get Attached
@#$#@#$#@
With this model I have tried to establish a real-life simulation of how girls and boys get attached. This model is very fundamental and is inspired by real life experience around me that girls tend to attach with people who are closer to them even though with a lower attractiveness. I believe that in daily life people are consistently making evaluation in partner selection and attach to the one with the relatively high evaluation.
@#$#@#$#@
Peloton Dynamics
@#$#@#$#@
This model simulates certain complex dynamics of bicycle pelotons. It shows three phases as a function of a changing speed ratio between riders "in the wind" and those behind in drafting positions. It ignores race strategy or team tactics, and supports the notion that peloton dynamics are largely self-organized and not driven by individual and team strategy, which are secondary factors.
@#$#@#$#@
Zombies Model
@#$#@#$#@
## THE "ZOMBIES EAT EVERYBODY" MODEL:

I built this model to have a little bit of fun with the idea of two competing, mutually competitive predators. Zombies are intended to remain a constant challenge to the human population, the environment randomized according to a set of fairly tightly constrained criteria. Humans have some hope of killing a straggling zombie or two, but will likely spend most of their time running and scavenging.

Over time, the humans are free to breed and mutate into the most survivable possible agents. Survivability is judged for this model on the number of ticks human agents are able to persist in each round. Genetic traits which influence survivability are 'courage' - the propensity to risk being bitten in order to get food &amp; ammo, and 'speed' - the rate at which humans are allowed to run from the shambling horde.
@#$#@#$#@
TermitIA
@#$#@#$#@
This model shows a novel approach using swarm intelligence specifically Termites in order to perform something named Reductions when you play quinielas on Futbol Soccer bets.

Also this model can be viewed as a brute force clustering using termites inspired algorithms
@#$#@#$#@
Robbery-with-qlearn
@#$#@#$#@
This model presents a simulation of street robbery based on routine activity theory. Criminals are divided into light and heavy criminals according to crime factor. Light criminals forms gang and do gang robbery. When they achieve crime factor greater than 5, they do heavy robbery. Light robbery gains half the wealth of victims. Victims are - people, women and kids. Women and kids are easy to rob. The presence of police avoids robbery.
@#$#@#$#@
admisiones_breeds-lists
@#$#@#$#@
The model tries to make a simple simulation of the behavior of the process of admission to the available undergraduate programs of the Universidad Nacional de Colombia-sede Bogota (National University of Columbia-Bogota), taking into account the changes that will be implemented starting in the second semester of 2013.
@#$#@#$#@
OSOSS1rc2
@#$#@#$#@
This is a model of informal online learning. OSOSS stand for online self-organizing social system. The phrase was coined by Wiley and Edwards in their 2002 paper regarding the way in which large groups of people manage to support each others' learning needs via the network
@#$#@#$#@
FamiliarTrafficDiversion
@#$#@#$#@
This project models the flow of traffic around a familiar 'diversion' scenario. Each car follows a simple set of rules: 1) Adhere to the speed limit; 2) If car ahead is stopped, stop; 3) If road ahead is closed, find available route; 4) If light is red, stop. 5) If light is green, go. The model demonstrates how small adjustments in the world can affect traffic flow, including phasing of traffic lights, acceleration/deceleration variables and road closures.
@#$#@#$#@
Lattice-Walking Turtles_15
@#$#@#$#@
Based on lattice walking turtles, this is a simplified model for mobile ad-hoc network MANET, with moving nodes (mobiles). Each node can have variable range of connection. this model is intended to be used later in social network group formation problem based on skills randomly provided to some nodes. currently, a basic flooding searching algorithm with ttl setting and count of nodes and query generators
@#$#@#$#@
HNG
@#$#@#$#@
This is a model of binary choice coordination network game between heterogeneous players. Players have preferences over one of the available options and best respond given the choices of their neighbors. Players have a threshold function which determines whether they choose the action they like (satisfactory) or the one they dislike (frustrated)
@#$#@#$#@
twitter
@#$#@#$#@
The Twitter model is trying to show Agent Based Simulation on when and why a person will or will not re-tweet a message that he/she received from his/her friends or social networks by applying the concept of Diffusion of Innovations.
@#$#@#$#@
Combustion of Methane
@#$#@#$#@
This model is designed to simulate the combustion of methane gas. Users can control the starting amount of methane, the ratio of oxygen to methane,and several other features designed to show how changing conditions can change the rate of reaction.
@#$#@#$#@
Peloton 2
@#$#@#$#@
In a peloton one central principle is that as cyclists' increase their power-output toward their maximum, it becomes harder to pass those in front. So, when cycling at low power-outputs, riders can pass others frequently at comparatively fast speeds. As this power-output level increases, riders pass others less frequently, they reduce their lateral movement, and the peloton begins to lengthen. At a certain power-output threshold, they cannot pass others at all, but by drafting they can keep up to those ahead, even if riders ahead are stronger. This model simulates phases that emerge from these principles.
@#$#@#$#@
Kaboom
@#$#@#$#@
This model is a version of the Atari 2600 video game Kaboom. The objective of the game is to have player-controlled buckets at the bottom of the screen catch bombs that are dropped by a turtle at the top of the screen. The turtle, known as the Bomber, exhibits random horizontal motion and periodically drops bombs. The buckets are controlled by the player, but can only exhibit horizontal motion.
@#$#@#$#@
DroneNET
@#$#@#$#@
This is a model of a decentralized goods delivery network managed through drones, designed to test some basic elements of its configuration and identify its topline functioning profile. The model uses three breeds of agents: pads, which just signal through their color whether they're available for landing (green), available only to empty drones (blue), or occupied by a drone (red); They have a capacity, which is the maximum number of packets that can be uploaded to the platform at the same time; packets, which are placed on platforms at random and have a destination platform; and drones, which fly around delivering packets. 
@#$#@#$#@
Axelrod_Cultural_Dissemination
@#$#@#$#@
Axelrod's Model for Cultural Evolution is an agent-based model described by Robert Axelrod in his paper: Axelrod, R. 1997,"The dissemination of culture - A model with local convergence and global polarization", Journal of Conflict Resolution 41:203-226. This model implements Axelrod's model with one extension: the agents can move. It is an agent-model designed to investigate the dissemination of culture among interacting agents on a society. Each agent can interact only with its four neighbors (von Neumann neighborhood).
Dynamics are based on two main mechanisms: (1) agents tend to chose culturally similar neighbors as interaction partners (homophily) and (2) during interaction agents influence each other in a way that they become more similar. The interplay of these mechanisms either leads to cultural homogeneity (all agents are perfectly similar) or the development of culturally distinct regions (multicultural society).
@#$#@#$#@
Phase Transition Noise
@#$#@#$#@
This simple model demonstrates a phase transition behavior emerging from the interactions among multiple agents in the presence of noise.
At a noise level higher than a certain threshold, the system generates symmetric behavior (e.g. vapor or melt of magnetization) or disagreement; whereas at a noise level lower than the threshold, the system exhibits spontaneous symmetry breaking (solid or magnetization) or consensus.
This provides some simple intuitions for understanding the impact of noise in communication networks on network behavior and the impact of noise (temperature) in phase transitions.
@#$#@#$#@
Peloton Simulation 3
@#$#@#$#@
Cyclists well know that as they increase their power-output toward their maximums, it becomes harder to pass those ahead of them. When cycling at low power-outputs, riders can pass others frequently at comparatively fast speeds.
As their collective power-output increases, riders pass others less frequently, they reduce their lateral movement, and the peloton begins to lengthen. At a certain output threshold, they cannot pass others at all, but by drafting they can keep up to those ahead, even if riders ahead are stronger.
As cyclists adjust their power-outputs, interesting changes in their collective behavior occur as the peloton shifts through observable phases.
The peloton motion that appears in this model is not created or led in any way by special leader cyclists. There are no Lance Armstrongs here. Each cyclist follows the same set of rules, from which collective peloton motion emerges.
@#$#@#$#@
Growth_Used_in_Chapter_and_Distributed
@#$#@#$#@
The Growth model is a stylized simulation of a rangeland with cattle feeding on grass.  Herders may practice wet season dispersal, where they graze broadly during the wet season and are confined areas near water in the dry season, or dry season dispersal, where they stay near permanent water in the wet season but then move further into reserved grazing lands in the dry season.  The benefits of those two methods may be compared.  The model was used in a chapter publication, Boone and Galvin (in press, anticipated in 2013) of a volume edited by Manfredo et al.
@#$#@#$#@
Smog
@#$#@#$#@
This model simulates the formation of photochemical smog over time. Nitrogen dioxide (NO2) and volatile organic compounds (VOC) are primary pollutants that are released into the atmosphere as a result of fossil fuel combustion. In the presence of oxygen (O2) and sunlight, they undergo chemical reactions that form ozone (O3) and photochemical oxidants (Ox), which are the principal components of smog.
@#$#@#$#@
Fisheries_and_Management_v3
@#$#@#$#@
This is a predator-prey model, with fishing boats as predators and minnows as prey and plankton as food source. The minnows also feed on plankton, which is continuously regenerated. The difference between this and other predator prey models is that there are options to (a) have the fishing boats hunt minnows (b) have the minnows try to escape from the boats and (c) let the minnows school. Plus there is the option of modifying the behaviour of the fishing boats by adding in no-fish reserves. There is quantitatively different population dynamics when each of these options is selected. This model therefore serves to show the versatility of agent based modeling in complex population dynamics.
@#$#@#$#@
snakesladders_v2
@#$#@#$#@
This model was set up to provide a working conceptual model of coral reef dynamics in the face of climate change. Climate change threatens a wide range of ecosystem processes that underpin the world's coral reefs. The implementation of conservation actions to manage fishing pressure and water quality has already shown resilience benefits, however ongoing public support is critical to ensure these and future actions can successfully counter the deleterious effects of climate change. Public understanding of resilience theory and the complexity of stochastic events effecting coral reefs is limited, in part, by the model format presented. Here we present a model used as a basis for the simple game known as 'Snakes and Ladders' to assist in the understanding of resilience potential and stochastic events in coral reef ecology.
@#$#@#$#@
OptionsMarket
@#$#@#$#@
This simulated options market creates a grid of traders who use the Black-Scholes formula to determine when to buy and sell options. Values such as the starting price and the risk free rate of interest can be adjusted by the user to see what effects different variables have on the market. The agents are arranged on the grid based on their level of "patience" (the range of the market they analyze) and "judgement" (how much they deviate from the Black-Scholes formula). The traders gain and lose money as they trade options with the Black-Scholes formula. Lighter green means success, lighter red means loss, and darker colors or black indicates small success or small loss. Successive markets are averaged into the main display in a Monte-Carlo type model
@#$#@#$#@
Track_and_Field
@#$#@#$#@
End of term course project. An examination of racing tactics in a track race.
@#$#@#$#@
MinimumWages
@#$#@#$#@
This model is a simple agent-based model of negotiations between potential employers and potential employees in an artificial economy in which minimum wages are expected to be introduced. In the current version both groups can have different sizes, and every employer can employ more than one worker. The current version makes a distinction between three employer types (fast food providers, providers of cleaning services and providers of simple construction services). The model is in some features inspired by the zero-intelligence constrained (ZI-C) traders from Gode and Sunder. The ZI-C traders cannot make a trade that will yield a negative profit, i.e., buyers cannot buy at a price higher than their buyer value and sellers cannot sell for a price below their seller cost. In contrast to that model, both partners in this model can adjust their expectations according to the experiences made by themselves and/or their neighbours within a user-defined radius.
@#$#@#$#@
PJ_Kelton4_10_queues
@#$#@#$#@
Imitates the discrete event simulation approach using agents.
The specification of the problem used in this example is:
Customers arrive at an order counter. Interarrival Law: exp(lambda = 10 min)
A single clerk accepts and checks their orders and process payments; service law: unif (8,10)
Upon completion this step, orders are assigned randomly to one of 2 available stock-persons; service law : unif (16,20)
Customers then leave the system.
Develop a model and experiment 5,000 min. Describe the experience of customers in terms of total time in the system.
A kaizen-team proposes to improve by changing the assignment policy of the stock-person following a FIFO PULL rule: each one of stock-persons pulls next order from a FIFO line.
Verify the improvement.
@#$#@#$#@
DiscreteLife5
@#$#@#$#@
An upgrade of the 2004 DiscreteLife (see below).
@#$#@#$#@
WSN-Project-20-Final-6
@#$#@#$#@
The model was designed to investigate the energy efficiency of multihop routing protocol for decentralized wireless sensor networks. The main question was how was the energy efficiency being achieved in networks employing multihop routing? What parameters gave the optimal energy savings compared to direct transmission? How is the network lifetime effected by changes of these parameters in the same network? The model has one two entities. Wireless sensor nodes and Data packets. The nodes are spread randomly in a 150x150 landscape. They have the following variables.Energy, Geographical Location, Channel State Estimation. Data packets have only one variable. Their size which is constant. The length of one time step is equivalent to one round of data transmission between a random source and destination node.
@#$#@#$#@
Educational Model of Speciation
@#$#@#$#@
This is a set of simulations designed to show how two populations become different species, through a process called speciation. There are two types of speciation: allopatric, which relies of geographical isolation, and sympatric, which relies on behavioral isolation. This simulation is designed with introductory biology students in mind, though no prior knowledge is required to explore.
@#$#@#$#@
version1_2
@#$#@#$#@
The model tries to illustrate the problem of maintaining common pool resources in a society with peoples of different attitudes towards the social benefit from serving common interest. In this frame the model introduces social persons and opportunistic free riders into the world which are all focusing one common good of limited number and limited operation level, the bicycles. The agents of different breeds (social persons and freeriders) are setup in an environment (grid), which contains ground, introduced by patches with the attributive operation-level of -1 and grey color, operating bicycles, set as patches with operation-level of 20 and green color and broken bicycles with operation level underneath 5 and of brown color. The breeds are distinguished through the different value of the state variable attributes, which is willingness-to-repair, their attitude. According to their attitude, the breed react differently on the state of the patch there are on and also the state of the patch (operation level) changes due to interaction with agents.
@#$#@#$#@
LLNL
@#$#@#$#@
Description.
@#$#@#$#@
RenKraut-SimulateOnlineCommunity
@#$#@#$#@
This model is an agent-based model that simulates member motivation and contribution in a conversation-based online community such as UseNet groups or web forums. Individual agents imitate members in an online community and can make decisions to read and post messages based on perceived benefits and costs of doing so. It can be used to run virtual experiments to develop theories about individual behaviors and social dynamics in online communities and to inform the design of real-life online communities. NOTE: this model requires NetLogo 3.1.5 to run, which can be downloaded here: http://ccl.northwestern.edu/netlogo/3.1.5/
@#$#@#$#@
Siste Mafia33, edited 2
@#$#@#$#@
This work simulates a market influenced by Mafia. The white agents are the storeowners; the black are the mafious and the blue represents the police ones. The patch is a simplification of the market, where the storeowners can obtain profits or not. When a mafious finds a storeowner, he tries to get money from this. When the police find a mafious, this one must pay a bribe for the police to don't be arrested. This simulation intends to find a way in wich the power of Mafia can be erased by social norms and new values in a community.
@#$#@#$#@
MEGanE SysDyn Netlogo
@#$#@#$#@
This is a very simplified version of the model 'MEGanE' published in the journal Agrociencia 16:2 (Faculty of Agronomy, Uruguay) by Dieguez et al.
The model presented as a dynamical system aims to represent the evolution of the relationship between the grass height  and animal weight (considering a constant stocking rate, no mortality or animal removal or reproduction). It is a preliminary version of the MEGanE studied as a dynamic model.
@#$#@#$#@
EmptyBinCity
@#$#@#$#@
This model simulates the garbage collection operations in part of a city grid.
BINS (agents) situated in the corners of blocks of a city (patches) are receiving waste units from local residents. The load increase step and the maximum capacity of the bins can be modified. Bin content increases randomly in a range defined by the load increase step on a hourly basis. When a bin reaches (and slightly exceeds) its capacity, it turns black and stops receiving more waste.
Garbage collection is undertaken by two different fleets of GARBAGE TRUCKS (breeds of agents). All trucks move around across the city road network with a speed of 1 road-patch/minute and have a maximum load capacity according to their type. PUBLIC (red) trucks' operation cost is defined on a time basis while PRIVATE (blue) trucks' operation cost is proportional to the collected waste units.
As soon as a garbage truck is full, its color turns black and is "teleported" to the north-eastern point of the city (yellow patch), where it dumps its waste. All empty garbage trucks return to duty.
@#$#@#$#@
virus 2
@#$#@#$#@
This model simulates the transmission and perpetuation of a virus in a human population.
@#$#@#$#@
Pond Microscopic
@#$#@#$#@
Based on the aquatic ecosystem, the micro level simulation is designed to build upon knowledge acquired from the Pond Macro simulation. It is intended for students to understand the influence of nutrient run-off on the quality of water and subsequent dip in levels of dissolved oxygen leading to sudden death of fish.
@#$#@#$#@
Pond Macroscopic
@#$#@#$#@
Based on the aquatic ecosystem, this simulation affords opportunities to explore the relationship between visible structures such as sunlight and algae and invisible structures such as nutrients and amount of oxygen and carbon-di-oxide present in the water.
@#$#@#$#@
Carbon Cycle
@#$#@#$#@
Based on the carbon cycle this simulation is intended to explore natural processes such as respiration and combustion, which increase carbon levels and acidity of ocean water leading to multiple problems in the marine ecology.
@#$#@#$#@
Fish Spawn
@#$#@#$#@
This aquatic based simulation is designed to highlight the concept of carrying capacity. Users are to determine how many fish can fit in a 10-gallon tank of water.
@#$#@#$#@
Wealth Distribution2
@#$#@#$#@
This is a extension of the Wealth and Distribution model developed by Uri Wilensky.  I have added a slightly progressive tax rate structure to distribute the wealth to other classes.  Also, if a certain class's resentment towards the other class exceeds some threshold, then the class will try to take control of the tax rate.
@#$#@#$#@
CoordinationAndSustainability
@#$#@#$#@
Much like Epstein and Axtell's Sugarscape, this virtual world is populated with agents which move around on a grid on whose patches food grows and grows back constantly, and over-harvested patches can regrow when seed floats in from neighbouring patches. Agents harvest and either eat or add the harvested food to their "wealth". Agents have a limited lifetime, and they can die from starving. Besides they reproduce. All of these actions satisfy their needs of survival, wealth, reproduction and information. Moreover they have a need of being influential which is an incentive to co-ordinate other agents. Co-ordination means that co-ordinating agents collect information from their (volunteer) subordinates and forward this information back to all their current subordinates which gives both co-ordinators and subordinates a wider range of vision such that their chance to move to more promising patches increases. The decision to co-ordinate, subordinate, end co-ordinating or end subordinating and all other decisions (to eat, to harvest, to move, to reproduce) depend on the expected utility of the respective action which in turn is calculated as a weighted sum of degrees of satisfaction of the needs mentioned above. The decision is probabilistic, such that the action with the least utility is never taken whereas the other actions are taken with a probability proportional to the expected utility.
@#$#@#$#@
PJ_beergame
@#$#@#$#@
The beergame is a classic in supply chain management training. It reveals the bullwhip effect due to system latency. This phenomenon is known as "Forrester effect": the variability of final downstream demand is amplified in a erratic way through the supply chain. This model is a construction of the classic example, the beer game, used in most supply chain training to discuss the Forrester effect.
@#$#@#$#@
Kelly
@#$#@#$#@
This model is a visual representation of diferentiation measures obtained using George Kelly's personal construct theory. The circles represent the Real Me (A) the Ideal Me (I), the Mother (M), the Father (P), the Brother/Sister (I), the Friend of the same sex (Ams) and the Friend of the opposite sex (Aso). The scale allows to adjust manually the draw to the available space. There is no control of impossible results. Inconsistent diferentitation measures may introduce errors
@#$#@#$#@
Dados2
@#$#@#$#@
Simulates the rolling of a dice. There is one agent for each possible result between 1 and 33. The Nth agent jumps forward each time you need N throws to obtain the six results. The objective is to estimate how many throws you need to obtain the six different faces. The statistical value is 14.7. This is an upgrade of the model "Dados", originally submitted by this modeler in December 2012
@#$#@#$#@
aacondro_football_v1
@#$#@#$#@
This is a first attempt to understand the concept behind computer-based football games using the ABM tool of NetLogo, with a wish that it would latter be useful for understanding on how we collaborate or compete to mitigate or adapt to climate changes.
@#$#@#$#@
PJ_freddie
@#$#@#$#@
AN INVENTORY MANAGEMENT EXAMPLE. One of the daily newspaper that Freddie sells from his newsstand is the "Financial XYZ". A distributor brings the day's copies of the Financial XYZ to the newsstand early in the morning. Any copies unsold at the end of the day are returned to the distributor the next morning. However, to encourage ordering a large number of copies, the distributor does give a small refund for unsold copies. Here are the Freddie's cost figures: Freddie pays $1.50 per copy delivered. Freddie sells at $2.50 per copy. Freddie's refund is $0.50 per unsold copy. Partially because of the refund, Freddie has always taken a plentiful supply. However, he has become concerned about paying so much for copies that then have to be returned unsold, particularly since this has been occurring nearly every day. To investigate this further, he has compiled the following record of his daily demand: Freddie sells anywhere between 40 and 70 copies on any given day. The frequency is distributed uniform (roughly equal each number in between 40 - 70).
The decision Freddie needs to make is the number of copies to order per day from his distributor. His objective is to maximize his average daily profit.
@#$#@#$#@
PJ_Dijkstra
@#$#@#$#@
Consider the following silly game to be played by a single person with an urn and as many white balls
and black balls as she needs.

To begin with an arbitrary positive number of balls is put into the urn, and as long as the urn contains two or more balls, the player repeats the following move: he shakes the urn and, without looking, she takes two balls from the urn; if those two balls have the same color she throws one black ball back into the urn, otherwise she returns one white ball into the urn.

Because each move decreases the total number of balls in the urn by 1, the game is guaranteed to terminate after a finite number of moves, and it is not difficult to see that the game ends with exactly 1 ball in the urn.

The question is: "What can we say about the color of that final ball when we are given the initial contents of the urn?".
@#$#@#$#@
Symptom_Spread_Model
@#$#@#$#@
This model is a representation of major depression according to a recently emerging view on the relations between symptoms. This view is called the causal network perspective. This model can be run in your browser.
@#$#@#$#@
Fracking_v13a
@#$#@#$#@
This model shows how an oil spill can percolate down through permeable soil. It was inspired by a similar model meant to be done by hand on paper (see "Forest Fires, Oil Spills, and Fractal Geometry", Mathematics Teacher, Nov. 1998, p. 684-5).The soil is modeled as a checkerboard of hard particles (gray squares) and semi-permeable spaces in between these hard particles (brown squares). (You may need to zoom in to see the individual squares.) Oil cannot enter the solid gray squares, but it may pass through the brown squares. Some soils are more porous ("holey") than other soils. In this model the porosity value of the soil determines the probability that the oil will be able to enter any given brown soil square. The model represents an oil spill as a finite number of oil "particles", or simply oil drops.The oil spill starts at the top of the view, and percolates downward.The leading edge of the oil spill is represented by red squares, and every square that oil has passed through (or "saturate") is shown as black. The oil drops sink downward through the soil by moving diagonally to the right or left, slipping between the hard gray particles
@#$#@#$#@
GraphingRationalFunctionsGame
@#$#@#$#@
The following will be a game for teaching students how to graph a rational function. The current model is a test model to see if the model can be run from a website. This will be replaced shortly with the game.
@#$#@#$#@
Schlieffen Logistics
@#$#@#$#@
This model simulates logistical elements of the opening weeks of the World War I.  Specifically, it contains a model of the rail system used by the Germans to supply their forces as they advanced through Belgium and into France from August 5 to September 7, 1914.  Since the German advance unfolded differently from their original plan (The Schlieffen Plan), the goal of this model was to analyze whether the original plan was viable from a logistical point of view.  To accomplish this goal, the model presents two simulation modes: one showing the original Schlieffen plan, and the other showing the way it actually unfolded in history. Designed for Georgia Tech course Modeling, Simulation, and Military Gaming (CSE/INTA 6742) with instructors Dr. Thom McLean (College of Computing) and Dr. Michael Salomone (School of International Affairs).
@#$#@#$#@
Location Game
@#$#@#$#@
This is a simple model of competing restaurants choosing where to locate in a strip shopping mall. The model supports a series of games, outlined below, that students can use to explore the principle of minimum differentiation aka Hotelling's Law. The purpose of this game is to gain experiential familiarity with the strengths and weaknesses of the principle of minimum differentiation as a model that explains the observed clustering of retail sellers at a central location.
@#$#@#$#@
War Guard Queen 2
@#$#@#$#@
This is a program meant as a simplistic model of two ant colonies at war. The colonies maintain a balance between number of soldiers, and number of guards. The target of both armies is to eliminate the enemy queen while protecting their own. The smallest turtles, the soldiers, meet and fight each other. A "battle" consists of the program using a random number generation to act as a coin flip. If one soldier wins the coin flip, the other dies. Guards have a protection program that keeps them surrounding the queen unless they "smell" and enemy soldier, in which case they follow the scent and kill the soldier. Once a guard kills five soldiers, it runs out of strength, and dies. The queen reproduces lost soldiers and guards when they die, and acts as a flag, when their queen dies, they can no longer re-produce, and are much more likely to lose.
@#$#@#$#@
Social influence in networks
@#$#@#$#@
Based on the famous bounded-confidence model by Hegselmann and Krause (2002), this program allows you to develop hypotheses about the effects of homophily and network structure on the outcomes of social-influence processes in networks. In particular, you can identify the conditions under which the influence process results in perfect opinion homogeneity (consensus) or opinion diversity (clustering).
@#$#@#$#@
Lattice Walking Turtles
@#$#@#$#@
Based on lattice walking turtles, this is a simplified model for mobile ad-hoc network MANET, with moving nodes (mobiles). Each node can have variable range of connection. this model is intended to be used later in social network group formation problem based on skills randomly provided to some nodes. currently, a basic flooding searching algorithm with ttl setting and count of nodes and query generators. the new feature is a simplified version of ALARM flooding algorithm for research simulation. The algorithms had many parameters fixed for simplicity and not all details of algorithms are implemented.
@#$#@#$#@
SudokuGames
@#$#@#$#@
This is a Sudoku Game in NetLogo. The copyrights of the original version belong to "William John Teahan". I have extended the game and have added new features like Solver , Hard level Option, Pre Place number Option to place random numbers,  Build Custom Maps options, Load and Save game options. Enjoy the game, use the code. But before modification give proper references to Mr William John Teahan and Me. 
@#$#@#$#@
Modelo 1.3.6.5
@#$#@#$#@
The Ricardian Model of International Trade.
@#$#@#$#@
PJ_hungarian_v2
@#$#@#$#@
This model implements a solution of the well-known Hungarian method in heuristics to deal with the assignment type of problems.
Important features are the use of the Future Event List concept to govern the flow of agents.
@#$#@#$#@
Kuhnian Paradigm Shift 2
@#$#@#$#@
This model was designed to look at Kuhnian Paradigm Shifts.
@#$#@#$#@
Astardemo
@#$#@#$#@
This model simulates an implementation of the A* path finding algorithm, for finding the shortest path from a source patch to a destination patch. The heuristic function used (h(n)) always gives the exact distance from an intermediate patch to the destination patch by employing the NetLogo primitive "distance". This exact heuristic replaces the admissible heuristic in the standard A* which drives path finding exactly in the direction of the destination. This takes place by choosing the next patches (nodes) for exploration which are not yet explored and have the least cost i.e. the smallest distance to the destination as compared to other patches that have not yet been explored. This enables the algorithm to always find an optimal path (least cost path) to the destination, if one exists.
@#$#@#$#@
PJ_TSP_heuristics_sep2013_V5
@#$#@#$#@
An ant colony optimization algorithm applied to the famous NP-hard TSP (travel salesperson problem).
@#$#@#$#@
WolfMoose
@#$#@#$#@
Update of the WolfMoose program I submitted in 2004, modified so it will run on the current version of NetLogo (kindly put a note in the original WolfMoose page to direct people to this one)
@#$#@#$#@
OptionsMarketWithJumps
@#$#@#$#@
Stock Options market simulator making use of Geometric Brownian Motion, Jump Diffusion, and the Black Scholes equation.
@#$#@#$#@
Bayes1D
@#$#@#$#@
It is possible in principle to infer world states from the individual spikes of sensory neurones.
This model is a simple one-dimensional toy model intended to illustrate the key concepts.
@#$#@#$#@
Spatial
@#$#@#$#@
It is possible in principle to infer world states from the individual spikes of a sensory neurone.
This model extends the concept in the simpler one-dimensional case to consider spatial distributions of spiking sensory neurones.
@#$#@#$#@
Drift
@#$#@#$#@
It is possible in principle to infer world states from the individual spikes of a sensory neurone.
This model generalises how to perform Bayesian inference if the state of the world under consideration is dynamic.
@#$#@#$#@
EcologicalConstraints
@#$#@#$#@
This model studies how ecological constraints can forbid or demand the evolution of neurones in a population of neurone-less animals. 
@#$#@#$#@
Information Cascades
@#$#@#$#@
This models studies the conditions under which information cascades can occur with signalling games between simple reinforcement learners.
@#$#@#$#@
Vulnerability_To_Depression
@#$#@#$#@
It is hypothesized that if someone is vulnerable to depression (i.e., symptoms are strongly connected), mild stress could be enough to trigger a cascade of symptoms that can eventually lead to a full-blown depressive episode (Cramer et al., submitted). This model is made to illustrate this effect of vulnerability. This means that this model predicts that a person that is vulnerable and develops a depression due to, for example, severe marital problems, will not recover automatically when the marital problems are solved. More is needed to trigger recovery from depression. Conversely, for someone that is resilient to depression (i.e., symptoms are weakly connected), mild stress cannot trigger a cascade of symptoms. Severe stress can lead to a full-blown depression, but when the stress subsides, the depression will subside too. This effect is also known as the hysteresis effect.
@#$#@#$#@
NatSelGame
@#$#@#$#@
This simulation models coevolution of a predator-prey sytem. It is based on the board game SIMULATING NATURAL SELECTION by Robert P. Gendron from Indiana University of Pennsylvania. The model incorporates the following elements of a natural system: Variability, heritability, competition, predation, carrying capacity and differential reproduction. Users can set the intial values for adaptation scores, variability of adaptation scores and population size. The simulation produces behaviors that demonstrate directional selection, the coevolution of traits, genetic drift and predator-prey population cycles
@#$#@#$#@
sync
@#$#@#$#@
This model explores the synchronization of pulse-coupled oscillators on complex networks when the network itself is influenced by oscillator dynamics.
@#$#@#$#@
knowledge homophily and expertise seeking beta2
@#$#@#$#@
This model is an adaptation to the homophily and opinion formation model by Michael MŠs and Andreas Flache. It models the opinion diffusion process in congressional committee environments. This adaptation only makes people influencable if they seek opinions from others. People seek opinions from others if they perceive that their knowledge level is lower than the average knowledge level of their alters. If that condition is met, then the agent is influencable.

The model assumes the ideological space on any given issue is polarized, but there is some overlap between parties in the ideological distribution. Democrats can take on a random value between 0 and 1. Republicans can take on a random value between 0.85 and 1.85.
The choosers can be used to generate networks with links between congressmembers and lobbbyists, networks in which congressmembers are only tied to congressmembers and lobbyists are only tied to lobbyists, and networks in which every lobbyist contact is replaced with an additional congressmember contact.

Lobbyists have perfect belief resistance, so they do not change their opinions. Notice how the addition of lobbyists to the model makes political agents settle into their final positions much earlier, creating gridlock. The addition of lobbyists also generally prevents consensus, but can create balkanized groups that are internally homogenous.

The code can be modified so that lobbyists are not polarized and have higher knowledge levels than committee members. In this scenario, the addition of lobbyists makes political agents settle into their final positions later, creating consensus.

The topology parameter can be interesting for modeling political parties, since it moderates the number of inter-connections between two relatively intra-connected groups.

This version also adds error terms for all of the opinion updates.
@#$#@#$#@
Opinion Diffusion in Congressional Committees
@#$#@#$#@
This model is an adaptation to the homophily and opinion formation model by Michael MŠs and Andreas Flache. This adaptation only makes people influencable if they seek opinions from others. People only seek opinions from others if they perceive that their knowledge level is lower than the average knowledge level of their alters. If that condition is met, then the agent is influencable.

The model assumes the ideological space on any given issue is polarized, but there is some overlap between parties in the ideological distribution. Democrats can take on a random value between 0 and 1. Republicans can take on a random value between 0.85 and 1.85.
The choosers can be used to generate networks with links between congressmembers and lobbbyists, networks in which congressmembers are only tied to congressmembers and lobbyists are only tied to lobbyists, and networks in which every lobbyist contact is replaced with an additional congressmember contact.

Lobbyists have perfect belief resistance, so they do not change their opinions. Notice how the addition of lobbyists to the model makes political agents settle into their final positions much earlier, creating gridlock. The addition of lobbyists also generally prevents consensus, but can create balkanized groups that are internally homogenous.

The code can be modified so that lobbyists are not polarized and have higher knowledge levels than committee members. In this scenario, the addition of lobbyists makes political agents settle into their final positions later, creating consensus.

The topology parameter can be interesting for modeling political parties, since it moderates the number of inter-connections between two relatively intra-connected groups.

This version also adds error terms for all of the opinion updates.
@#$#@#$#@
VirtualCryptModel020413G
@#$#@#$#@
This computational model simulates the stochastic cell dynamics of normal human colon crypts. The model was calibrated with measurements of the numbers of stem cells, proliferating cells, and differentiated cells in human biopsy specimens. It has been used to simulate the initiation and treatment of colon cancer. It can be used for in silico experiments by changing model parameter values at the user interface. A more complete description of the model and simulation results are available in the publication R. Bravo, R. and D.E. Axelrod, Theoretical Biology and Medical Modeling 2013, 10:66, http://www.tbiomed.com/content/10/1/66.
@#$#@#$#@
MARS Migration
@#$#@#$#@
a mars exo-migration model
@#$#@#$#@
BRADFORD PD PUBLIC GOODS GAME FULL 1-31-14 NETLOGO
@#$#@#$#@
This model is derived from and inspired by Bowles and Gintis, "A Cooperative Species: Human Reciprocity and its Evolution" (2013: 64-66).  This model contains two games: an iterated Prisoner's dilemma game, and a Public Goods game consisting of N_groups each of n_size. Generally speaking, the purpose of the model is to see under what conditions "cooperation" (or "altruism") will prevail given self-interested agents. It involves the concepts of multi-level (group) selection and inclusive fitness.
@#$#@#$#@
BRADFORD SOCIAL NORMS 1-31-2014 Emperors Dilemma
@#$#@#$#@
This model tests under what conditions people will not only comply with norms they privately disbelieve (i.e. 'FALSE COMPLIANCE'), but also when they will actively enforce them (i.e. 'FALSE ENFORCEMENT').
@#$#@#$#@
Astardemo1
@#$#@#$#@
This model simulates an implementation of the A* path finding algorithm, for finding a path from the source patch to the destination patch. The heuristic function used (h(n)) always gives the exact distance from an intermediate patch to the destination patch by employing the NetLogo primitive "distance". This exact heuristic replaces the admissible heuristic in the standard A* which drives path finding exactly in the direction of the destination. This takes place by choosing the next patches (nodes) for exploration which are not yet explored and have the least cost i.e. the smallest distance to the destination as compared to other patches that have not yet been explored. This enables the algorithm to always find an optimal path (least cost path) to the destination, if one exists. 
@#$#@#$#@ 
Pandoran Ecosystems
@#$#@#$#@ 
If you have ever seen AVATAR and the various creatures, this model simulates the ecosystem. Creatures all come in multiple colours so you can pick out more successful.
@#$#@#$#@ 
El Farol Attack of the coin flippers
@#$#@#$#@ 
This is an extension to the El Farol bar problem. This model includes a random strategy to show that guessing the number of patrons at the El Farol bar can be an optimal strategy.
The model builds heavily on Uri Wilensky original NetLogo implementation of El Farol. El Farol was originally put forth by Brian Arthur (1994) as an example of how one might model economic systems of boundedly rational agents who use inductive reasoning.
@#$#@#$#@ 
Nanjing_CI_SIM_27_Nov_2013
@#$#@#$#@ 
To examine the dynamics between the interaction of the development of creative industries and urban spatial structure
@#$#@#$#@ 
adverselockinmodel2
@#$#@#$#@ 
A Model of Innovation and Diffusion, where firms innovate using a genetic algorithm to solve a technological bottleneck. Adopters make decision based on Technological Expectations and Rigid Network Constraints.
@#$#@#$#@ 
rescue the princess
@#$#@#$#@ 
This model demonstrates goal-driven behaviors. The character (knight) can perform several interactions which are hierarchized so as to make it search and reach its goals. Basically the main goal of the knight is to rescue the princess which is somewhere in the maze. The knight uses a stack of goals so as to execute the appropriate actions. The knight is also endowed with personality traits which influences the interactions that are chosen in a given situation and thus introduces diversity in the outcome of the simulation. This implementation relies upon the IODA extension for NetLogo which allows the definition of declarative interaction rules for the design of behaviors.
@#$#@#$#@ 
Technology diffusion ABM
@#$#@#$#@ 
This model simulates technology diffusion. It postulates a duopoly with heterogeneous consumers and includes several interface variables that control
<br>
  * the number of buyers and their preference distribution;<br>
  * buyers' sensitivity to local or global social pressures;<br>
  * the frequency and distribution of innovation activity;<br>
  * firms' advertising efficiency;<br>
  * buyers' mobility (a proxy for network randomness).<br>

The model outputs the overall technology diffusion curve and diffusion curves for the competing brands and products. Also, it reports the effect of local/global social pressures on technology adoption decisions.
@#$#@#$#@ 
epiDEM plus baboon
@#$#@#$#@ 
Amendments to the Copyrighted epiDEM model in the Netlogo Library.  Display basic SIR model of a baboon system where rainfall promotes disease spread.
@#$#@#$#@ 
Extinction of Homo Economicus
@#$#@#$#@ 
A thought experiment to test Homo Economicus ability to survive natural selection.
@#$#@#$#@ 
Checkers
@#$#@#$#@ 
Checkers model AI vs. AI for simulating game strategies.
@#$#@#$#@ 
The Mafia Model - Interaction between police, mafia and storewoners
@#$#@#$#@ 
Mafia model
@#$#@#$#@  
Plant Community Dynamics 
@#$#@#$#@  
Explore the joint effects of habitat fidelity and dispersal distance in a simple plant community
@#$#@#$#@  
Sunshine or Shield Model
@#$#@#$#@ 
Do secret voting procedures help or hinder legislative bodies seeking to hold their own members responsible for wrongdoing? Drawing on parameters from the Brazilian case, this model illustrates how voting decisions are built from individual calculations into institutional accountability processes, shedding light on the contingent nature of accountability. 
@#$#@#$#@ 
Day and Night 
@#$#@#$#@ 
BRADFORD Sakodas Model of Social Interaction 6-25-14
@#$#@#$#@
This is based on Sakoda's 1971 paper "The Checkerboard Model of Social Interaction" in "The Journal of Mathematical Sociology"- the same edition in which Schelling's model of segregation was first published. In this model, there are n groups, each with 2 attitudes: an "in-group" attitude towards its members, and an "out-group" attitude towards everybody else. currently, these attitudes can take on one of 3 values (+1, 0, and -1). On each turn, each agent decides to move one patch or remain in place, based on which patch location has the highest value. The value of each patch is determined by the following algorithm:<br>
Patch_value = Sum (Vj / (Dj ^ (1/w))),<br>
where Vj is either +1, 0, or -1 (i.e. the 'value' for other turtle j), D is distance to that turtle, and "w" is the parameter "Importance of Far Away Agents". Basically, the potential patch location calculates this for every other turtle and then sums them to get the overall or total value for that patch. Then, the turtle picks the patch with the highest value and moves to it.<br>
This model extends Sadoka's original model in several ways. First, you can choose more than two groups now. Second, you can choose the population level you want (in the original, there are only 6 agents per 2 groups).
@#$#@#$#@
BRADFORD Expectations Luhmann 6-26-14
@#$#@#$#@
This is a reconstruction of a study by Peter Dittrich, Thomas Kron and Wolfgang Banzhaf (2003) entitled "On the Scalability of Social Order: Modeling the Problem of Double and Multi Contingency Following Luhmann" available here: http://jasss.soc.surrey.ac.uk/6/1/3.html

The purpose of the model is to see under what conditions can expect 'social order' to emerge. The primary variables of interest are 1. population size: will social order appear when 'double contingency' is 'scaled up' to multiple contingencies? 2. The 'strategies' that the agents adopt: will EE or EC be more successful at generating order? There are three different measures of social order which appear in the graphs.

Each agent has two means of reducing uncertainty ('motivations') when interacting with others: expectation-expectation (EE) and expectation-certainty (EC).
EE refers to the efforts of an agent (ego)to make his/her responses to a particular message from alter predictable and hence consistent with egos prior responses. EE refers to egos expectation of alters expectation of ego. Agents can generate certainty by conforming to the expectations of others. Because the expectations of others cannot be observed, however, ego must anticipate that others will expect them to respond as they have in the past.
EC refers to the efforts made by agents to reduce the uncertainty of alters responses. Rather than basing ones own behavior on the (anticipated) expectations of alter as in expectation-expectation, ego instead selects behaviors (or messages) that will elicit the most predictable responses.
Expectation-expectation orients behavior according to the query How do I usually respond in these situations?, whereas expectation-certainty orients behavior according to the query How do you normally respond to my actions? The two behavioral algorithms are sometimes conflicting. 
@#$#@#$#@ 
BRADFORD MINDING NORMS Hunting for Norms 7-1-14 
@#$#@#$#@ 
This simulation compares how different types of agents (social conformers and norm detectors) converge on a particular action while interacting across multiple settings. Social conformers adopt the most popular action in a given situation. Norm detectors both observe the actions of other agents and also send and receive messages about those actions. Norm detectors recognize an action as a norm if and only if: (a) the observed compliance of an action (i.e. the % adopting the act in a social setting) exceeds their personal threshold, and (b) accumulated force of messages (i.e. the Ômessage strengthÕ) concerning that action exceeds 1. Once an action is regarded as a norm for a given social setting, a Norm Detector will adopt it regardless of what other agents are doing, although it is possible for Norm Detectors to have multiple norms for a given setting.
This is a replication of the model from chapter 7 entitled ÒHunting for Norms in Unpredictable SocietiesÓ in Minding Norms: Mechanisms and Dynamics of Social Order in Agent Societies, Eds. Rosaria Conte, Giulia Andrighetto, Marco Campenni 2014, Oxford University Press.  
@#$#@#$#@ 
Neuromuscular junction ABM - Final NetLogo Code 
@#$#@#$#@ 
One of the leading causes of death and illness within the agriculture industry is through unintentionally ingesting or inhaling organophosphate pesticides. Organophosphate intoxication directly inhibits acetylcholinesterase, resulting in an excitatory signaling cascade leading to fasciculation, loss of control of bodily fluids, and seizures. Using a discrete, rules-based modeling approach in NetLogo, we have designed a model of the neuromuscular junction. This model includes acetylcholinesterase, the nicotinic acetylcholine recep-tor responsible for signal transduction, a single release of acetylcholine, organophosphate inhibitors, and a theoretical allosteric medical countermeasure. By using an agent-based model, we have parameterized the system to consider the molecular reaction rate constants as opposed to apparent macroscopic rates used in differential equation models. Our model demonstrates how the cholinergic crisis can be mitigated by therapeutic intervention with an a
 llosteric acetylcholinesterase activator. Our model predicts signal rise rates and half-lives con-sistent with in vitro and in vivo data in the absence and presence of inhibitors. It also predicts the effica-cy of theoretical countermeasures acting through three mechanisms: increasing catalytic turnover of ace-tylcholine, increasing acetylcholine binding affinity to the enzyme, and decreasing binding rates of in-hibitors. Our model suggests that developing a countermeasure capable of reducing inhibitor bind-ing, and not activator concentration, is the most important parameter for reducing OP intoxication. 
@#$#@#$#@