NetLogo User Community Models
How to share your models
We encourage users to share your models with the NetLogo user
community. You may upload your model through our model upload
page. The web site will automatically create a web page for your
model. Contributed models are credited to their authors.
We also have a model URL
submission page. Use it if you prefer to host your model on an
external web site.
These models are contributions from the user community and are not included with NetLogo. These models are authored by the individual contributor and are not checked by the CCL staff.
| ||Collaborative demand forecasting by Valentas Gruzauskas
Supply chain resilience has gained more importance in recent years due to the trend for e-commerce. The industry has a tendency to sell products in low quantity, with high demand variation. To increase the resilience of the supply chain, demand forecasting is necessary. The model compares two approaches towards forecasting. One case focuses on forecasting only on individual distributorÕs history and another case considers the possibility to share information and forecast on all distributorsÕ histories.Key interests: Extension R, Neural network, Extreme learning machine
| ||Model 1 - Spread of content in a network by Noam Drory
This model studies how a content is spread in a network with regard to its uniqueness and offensiveness. once the initial parameters were set, the centered member of the graph starts spreading the content (if he isnt indifferent to it) to one of his neighbors , the neighbor then spreads it to one of his neighbors, and so on. If the agent has either a positive or negative opinion on the content, his or hers opinion will be taken to account (meaning, it will be counted). Thus we can simulate content spreading and the reactions of the network to it.
| ||Model 2 - Social Conception of content by Noam Drory
This model studies how individuals on a network affect one another in regard to content delivery, and particularly, offensive content. each interaction of an agent with its neighbor, can, with some probability, cause the neighbor to change his or hers opinion and action regarding the content (Namely, being indifferent to it, forward it without taking a stand, or respond positively or negatively to it). Some agents, have fixed opinions and cannot be moved. Nevertheless, if an agent isnt fixed, it is harder to change his stand if his mind is set to a strong stand (Positive or Negative) rather than to a soft one (Indifferent or Distributer).
| ||DiscreteEventSimulation_QueuesServers by Nick Bennett
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.Note: This model requires NetLogo 6.0 or higher.
| ||Colon_Crypt_Model_110514_G by David E. Axelrod
Colon Crypt Model 110514 G.nlogo. Simulates human colon cancer initiation, therapy, and prevention. Chemotherapy of heterogeneous and drug resistant early colon cancers can be simulated. Includes interface, code, and detailed information. Useful for in silico experiments directly from the user interface. Illustrates and plots the cell dynamics of stem cells, transient amplifying cells, differentiated cells, and mutant cells. Data can be saved in spreadsheet format for producing graphs or further analysis. Runs on NetLogo version 4.1.3 or 5.3.1. Axelrod DE, Vedula S, Obaniyi J. Effective chemotherapy of heterogeneous and drug-resistant early colon cancers by intermittent dose schedules: a computer simulation study.Cancer Chemother Pharmacol. 2017 May;79(5):889-898. doi: 10.1007/s00280-017-3272-2. Epub 2017 Mar 25. PubMed PMID: 28343282. http://rdcu.be/qn25.
| ||Life of Pi(gs) by Desi Suyamto & Aritta Suwarno
Portraying the life of pigs in a pig-house in every minute, aiming at estimating the pigs' welfare.
| ||Evolution of Sex by K N Crouse
| ||SegregationExtended by Klaus G. Troitzsch
This project models the behaviour of two groups of turtles (red and green, red being the minority) in virtual world. Turtles prefer to live in the neighbourhood of turtles of the same colour. Whether they are happy at their current patches depends on the percentage of turtles of the same colour in their Moore neighbourhoods and on their individual tolerance thresholds: If %-similar-seen is greater or equal %-similar-wanted, they are happy. In this extended version of earlier models, the thresholds of the individual turtles can be different both within and between subpopulations, and they can change depending on the current neighbourhood. The classical version with identical and constant thresholds for all turtles and subpopulations of equal size can, of course, also be simulated.
| ||AntsAtWar by John Thomas
Ants at War models two ant swarms at war illustrating the Invasive Ant Syndrome
| ||Airfoil Analysis by Lincoln Berkley
This model simulates in two dimensions the motion of air around an airfoil shape, such as an airplane wing. It uses the motion of individual particles according to the Ideal Gas Law and elastic collisions, which are similar to the behavior of molecules in the real world. It can be used to analyze the effects of different airfoil shapes or environmental conditions, such as altitude or airspeed, on the forces on the airfoil and the turbulence patterns it creates. It also shows how the general principles of fluid dynamics come from the motion of individual particles.
| ||Fire in the forest by Roland, B., Kampis, G., Karsai, I.
This model explores the dynamics of an animal/tree/fire ecosystem with random fires.The result of this model has been published in Ecological Complexity 28 (2016): 12-23.
| ||EIPSymb - Site version by Gabriel Couto Mantese
| ||El Farol Network Congestion by Uri Wilensky
El Farol is a bar in Santa Fe. The bar is popular, but becomes overcrowded when too many patrons attend. Patrons are happy when less than a certain amount of patrons attend, say 60 for example, but they are unhappy when more than some other amount of patrons attend, say 70. What will happen as time passes and people have pleasant or unpleasant experiences?Is it always true that the more a bar is popular, the higher its attendance? Does it makes sense to say a bar has its ups and downs, but on the whole its stable?This model problematizes a seemingly simple situation of social interaction to reveal that it is not that simple. Working in this model, we encounter and appreciate the inherent coordination challenges that can arise in complex dynamic systems involving agents with intention and specified needs and criteria of satisfaction. Can patrons of a bar somehow self organize to optimize overall satisfaction?
| ||Landscape Diversity by Ervin Wirth
The Landscape Diversity model uses scout agents, whose task is the collection of different land cover types in a discovery time. After the simulation period we obtain an integral value, which can serve as a metrics to the landscape diversity phenomena. Higher potential values imply more complex landscape structure.
| ||Genetic Inheritance by Emma
This model is a simplistic simulation of the spread of a genetic disease with an autosomal recessive inheritance pattern in a small, isolated human population. It illustrates how allelic frequencies vary from generation to generation.Genetic inheritance has risen to prominence as medical professionals have realized the implications of family health knowledge. Genetic diseases, indicators of heart, blood. and addiction problems, and even certain cancers can be predicted and measures can be taken to prevent the onset of these medical issues. Although genetic diseases are considered rare, twenty percent of all infant deaths are due to birth defects and genetic conditions.There are between 6,000 and 18,000 known single-gene disorders, affecting one in every 200 births, and only a small fraction of these have treatments. Additional study in this field could lead to the production of a wider range of more effective treatments and perhaps even cures for genetic diseases.The model examines the effects of certain variables on the allelic frequencies of the gene pool. The user controls several aspects of the child-bearing relationships modeled. Exploration of these variables can provide insight into the genetic trends scientists have observed in natural populations and show why recessive genes cannot become completely extinct.
| ||MAP-K Final by Edgar Manzanarez-Ozuna, Dora-Luz Flores, Alberto Abaroa, Carlos Castro, RubÃ©n CastaÃ±eda-MartÃnez
In this model, a cascade of biochemical reactions that are part of the MAPK pathway inside the cell are simulated.The MAPK pathway is a signal transduction network that mammals, plants and yeast use for intracellular signalling. This network is a small portion of the EGF pathway. After signalling molecules have linked up to receptors in the cellular membrane, the biochemical reactions of the MAPK pathway take place inside the cell. Mitogen-activated protein kinases (MAPKs) are involved in this pathway by mediating the signal transductions.
| ||Coop4SWEEEM_1-0_SPANISH by Sandra Mendez-Fajardo
ABM-Simulation about WEEE management - Coop4SWEEEM (Cooperation For Sustainable WEEE Management) simulates the influence of incentives on consumers of Electrical and Electronic Equipment. Based on the incentive, consumers decide to deliver (ot not) the waste to the post-consumer program (PCP). At the same time, the PCP works thanks to the cooperation between related producer (who assemble or import the device) and distributor (who sell devices). It was implemented in NetLogo 5.3.0
| ||Cipolla's Stupid World by Andrea Cossu
An agent-based simulation of Cipolla's stupidity theory. Agents interact following Cipolla's five Basic Laws of Human Stupidity.
| ||EONOERS by Klaus G. Troitzsch
EONOERS is an event-oriented version of my model simulating an extortion racket system whose agents (shops, criminals, police, consumers) calculate the salience of extortion related legal and social norms from each other's norm invocations.
| ||EditedCode-CarCruise by Abha Trivedi
Edited the old style code syntax in car-cruise model for latest version of NetLogo
| ||ALModel by Tomas Nachazel
NOTE: The ALModel requires support files in order to run correctly. Download the .zip file here.
Artificial life model (ALModel) is an ecosystem simulation with autonomous agents (individuals) in a dynamic environment. Like any other artificial life model, it allows exploring real natural phenomena, emergence, and evolution within hours of runtime. It is edifying to study emergent processes through the observation of evolving intelligent agents. Natural selection reveals the main directions of evolution and specialization of various species after several generations of agents in the simulation. This model was also developed for testing of artificial intelligence (AI) of individuals. Currently, two AI models are included: a single large Fuzzy cognitive map (FCM) and an FCM combined with Analytic hierarchy process (AHP).
| ||Mobility and extinction risk in human-altered landscapes by Amanda E. Martin
This model was designed to simulate the evolution of dispersal characteristics and species mobility in a landscape context, and the population response to habitat loss. Here mobility refers to the tendency to leave the current home range or territory (i.e. emigration) and the likelihood of settling in a different habitat patch (i.e. immigration). In particular, the model was used to test four hypotheses that might explain contradictory findings on the role of mobility in extinction risk, because in some empirical studies mobility appears to increase species extinction risk, while other studies report the opposite.The four hypotheses were:Metric type hypothesis: The mobility-risk relationship depends on how you measure mobility. This is because extinction risk increases with increasing mobility when mobility is measured as emigration, but decreases with increasing mobility when mobility is measured as immigration.Metric context hypothesis: The most mobile species (whether measured by emigration or immigration) in unaltered landscapes are least mobile in human-altered landscapes, so the relationship between mobility and extinction risk is opposite when mobility is measured in unaltered and altered landscapes.Metric range hypothesis: The mobility-risk relationship is ?-shaped, thus the mobility-risk relationship will be apparently positive when the study includes sedentary species to moderately mobile species, but the mobility-risk relationship will be negative when the study includes moderately mobile species to highly mobile species.Landscape context hypothesis: The mobility-risk relationship depends on the landscapes of the studied species. This is because some landscape structures drive evolution of dispersal characteristics that increase both mobility and risk, while others drive evolution of characteristics that increase mobility and decrease risk.
| ||MIMICS v-CSI by Carlos Barra, Enrique Canessa, Sergio E. Chaigneau
MIMICS purports to simulate a social group that uses two contrasting abstract concepts to communicate about a given situation. Instead of viewing concepts as the result of an inductive process that extracts properties and their statistical structure from the environment, MIMICS views abstract concepts as subjective points of view, and sees communication as an attempt at inferring other peoples' subjective points of view. Furthermore, MIMICS assumes that abstract concepts require explicit teaching to be learned.
| ||Musical Chairs REVISITED by Andreas Angourakis
This Agent-Based model intends to explore the conditions for the emergence and change of land use patterns in Central Asian oases and similar contexts. Land use pattern is conceptualized as the proportion between the area used for mobile livestock breeding (herding) and sedentary agriculture (farming), the main forms of livelihood from the Neolithic to the Industrial Revolution. We assume that these different forms of land use interact in recurrent competitive situations, given that the land useful for both activities at the same time is limited and there is a pressure to increase both land uses, due to demographic and/or economic growth.
| ||QuotaAbolition by Diti Oudendag
| ||Evolution of boundary-crossing behavior by Amanda E. Martin
This simulation model was designed to simulate population dynamics and the evolution of the boundary-crossing response in a landscape context. The boundary-crossing response is the tendency to cross habitat boundaries, i.e. when a dispersing individual encounters a habitat boundary, does it turn back into habitat, or cross into non-habitat (also called matrix)?
| ||CompositeCollectiveDecisionMaking by Tomer J. Czaczkes
This model models the collective foraging of an ant colony in an enviroment with multiple semi-permenant and replenishing food sources. This may, for example, aphid colonies, flowers, or extra-floral nectaries. The model is designed to explore how two types of information - social (in the form of pheromone trails) and private (in the form of route memories) affect colony level foraging.
| ||Loop de Langton 2 by JAIME LUIS TORRES FLÃREZ
Loops de Langton son una especie particulares de la vida artificial en un autómata celular creado en 1984 por Christopher Langton. Se componen de un bucle de células que contienen información genética, que fluye continuamente alrededor del bucle y a lo largo de un brazo (o seudópodo), que se convertirá en el bucle hija. Los genes instruyen a hacer tres giros a la izquierda, completando el bucle, que luego se desconecta de su matriz.
| ||FINAL by Abhishek Bhatia
Genetically optimized ACO inspired PSO algorithm for DTNs
| ||HB-SOTL_8_10 by Pedro S. RodrÃguez-HernÃ¡ndez & Juan C Burguillo-Rial
HB-SOTL is a model of traffic moving in a city grid. It allows you to control traffic lights and global variables, such as the speed limit and the number of cars, and explore traffic dynamics. In our model, cars have a source and a destination, roads can have one or two directions, each of which can can have one or two lanes. We add new control methods, namely hb-sotl, hb-comm-sotl, QL-sotl, and LA-sotl.
| ||PJ_petri_DiningPhilosophersR04 by jose costas gual
As can be seen in the INFO tab inside the enclosed model, this exercise is a Petri net approach to model the "Dining Philosophers" case that can be taken from the Sample Models / Computer Science.The interest of using Petri nets is that one canvas is devoted to the model itself, and the other is used for the animation.
| ||Sierpinski2015 by Milos Adamovic
This is model based upon the Sierpinski model that exists in NetLogo models library, but is has some options added to it.
| ||SNN_ARTIFICIAL_INSECT_MODEL_NETLOGO by Cristian Jimenez Romero
The presented Spiking Neural Network (SNN) model is built in the framework of generalized Integrate-and-fire models which recreate to some extend the phenomenological dynamics of neurons while abstracting the biophysical processes behind them. The Spike Timing Dependent Plasticity (STDP) learning approach proposed by (Gerstner et al. 1996, Markram et al. 1997) has been implemented and used as the underlying learning mechanism for the experimental neural circuit.The neural circuit implemented in this model enables a simulated agent representing a virtual insect to move in a two dimensional world, learning to visually identify and avoid noxious stimuli while moving towards perceived rewarding stimuli. At the beginning, the agent is not aware of which stimuli are to be avoided or followed. Learning occurs through Reward-and-punishment classical conditioning. Here the agent learns to associate different colours with unconditioned reflex responses.
| ||Ants2015 by EnÃ©e Gilles
Ants die and reproduce. They carry energy and it exists two species of ants that fight for their dominance in a simple way.
| ||HUMANIÌA (3) by Nadya GonzÃ¡lez-Romero
| ||CamEncounter_v9.1_20151112 by Kevin Blecha
CamEncounter-basic is a model to simulate the process of an animal agent encountering a camera traps field-of-view (FOV). The purpose is to demonstrate how factors of home range size, movement characteristics, abundance, camera FOV dimensions, and camera triggering delay period contribute to the rate at which an animal encounters the camera.
| ||Axelrod - Network by Daniel Diermeier
This model simulates how people become similar through interaction. The idea is based on Robert Axelrods Dissemination of Culture (1997). In his paper, Axelrod notes that one universal feature of culture is that it is something people learn from each other and makes two assumptions: 1) People are more likely to interact with similar people, and 2) people become more similar after interactions. He goes on to cite three principles upon which his study is based on: 1) Agent-based modeling, 2) no central authority, and 3) adaptive (as opposed to rational) agents.
| ||Confident Voter - Network by Daniel Diermeier
This simulation models the Confident Voter model discussed in Volovik and Redner (2012). The Confident Voter model studies how individuals change opinion through interaction. Agents interact with their neighbors and adjust their opinion accordingly. Two adjustment procedures are studied: the Extremal Voter Model and the Marginal Voter Model.
| ||Heterogeneous Voter - Network by Daniel Diermeier
In Heterogeneous Voter Models (2010), Masuda, Gilbert and Redner introduce a heterogeneous voter model where agents have their own intrinsic rate to change opinion, reflecting the heterogeneity of real people. This model simulates their findings by studying how people adjust their opinion between multiple choices. The model simulates three different mechanisms for opinion adjustment: Ising, Voter, and Majority.
| ||Ising - Network by Daniel Diermeier
This model studies how social decision, known as magnetization, changes over time. Social decision is modeled as the average opinion of all agents. Agents have one of two opinions. They adjust their opinion over time based on their current opinion, the opinions of their related agents, and the global ease of opinion change. As agent opinion changes, so does social decision.
| ||Potts - Network by Daniel Diermeier
This model studies how social decision, known as magnetization, changes over time. Social decision is modeled as the average opinion of all agents. The number of potential opinions varies. Agents adjust their opinion over time based on their current opinion, the opinions of their related agents, and the global ease of opinion change. As agent opinion changes, so does social decision.
| ||Social Consensus - Network by Daniel Diermeier
This model studies how public speaking or announcements affect social decision via an influential speaker. Social decision is measured by the opinions present in the network of agents. Speakers try to influence listeners to match their opinion. In this situation, some agents are committed and will not change their opinion no matter what opinion the speaker has.
| ||AIDS by bendaoud
| ||Day&Night by David Weintrop
| ||Boomshakalaka_shelton-atagi-keene-ross by Delia S. Shelton, Eriko Atagi, Justin R. Keene, Travis Ross
This is a model of the internet game Boomshine created by Danny Miller. You, the player, have one opportunity, a boomshot, to click and create the longest chain reaction possible or a set number of explosions to achieve an estabilished goal. This requires the player to monitor the behavior of the circular turtles and choose an optimal boomshot location.
| ||AVI by Mingsheng Tang
| ||Predator, Prey, Poison by Stephen H. Jenkins
Predator, Prey, Poison is modified from Wolf Sheep Predation in the Biology section of Sample Models of the NetLogo Models Library. I use coyotes and rabbits to illustrate predation because this is a natural predator-prey interaction that occurs wherever coyotes and rabbits coexist. The model includes the option of introducing a poison to some patches of habitat that kills both predators and prey during part of a simulation run. I discuss the model in detail in Chapter 6 of Tools for Critical Thinking in Biology, by Stephen H. Jenkins, to be published in April 2015 by Oxford University Press.
| ||NOERS by Klaus G. Troitzsch
This model of an extortion racket system introduces norm and utility oriented decision making by extorters, their victims (shop owners), the police and consumers.
| ||Flocking-softcontrol by Jing Han
A special agent-shill, which is treated as a normal agent by normal ones, is added into the flocking. User can intervene the flocking behavior through controlling the shill.
| ||NitrificationModelRutgersABedit by Annette Brickley
Nitrification in an aquarium: Cindy Hmelo-Silver of Rutgers Univ. created the original model for RepTools. It has been edited here to make it available to teachers for a professional development workshop.
| ||Spiranimator by David Slauson
Spiranimator creates animated and somewhat hypnotic spiral patterns by making incremental changes while repeatedly drawing line segments. After each spiral pattern is drawn the model waits briefly and then draws the pattern again, but from a slightly different starting angle. The result is an animated spiral pattern. Results are often surprising and sometimes quite artistic.
| ||Spiralator by David Slauson
The "Spiralator" model generates interesting cross-hatched spiral patterns by making incremental changes while repeatedly drawing line segments. Results are often surprising and sometimes quite artistic.This is a simple model using a single turtle and thus provides a good starting point for learning to program with NetLogo. Despite its simplicity it produces interesting variations, even when settings are altered very slightly.
| ||AVI+ by Mingsheng TANG
| ||Net_TDMA - by Kumud Wasti
| ||Radio_wireless by Kumud Wasti
| ||Forex by Marjo Kaci
The core of this simulation will be that of analyzing the simulation of the spot exchange rate EUR/USD and that of the Future exchange rate. The interest rate theory is telling us that the interest rate differential between two countries is equal to the differential between the forward exchange rate and the spot exchange rate. Interest rate parity plays an essential role in foreign exchange markets, connecting interest rates, spot exchange rates and foreign exchange rates. Therefore, interest rates of the two currencies have a considerable influence and we will see how variations of these interest rates will affect the exchange rates.
| ||Montecarlo circle by Antonio Hoyos
Transaction Costs in Financial Market
| ||Curb Parking Simulation Model by Yanan Xin
A model designed to examine the influence of Intelligent Parking Info System and Land Use Diversity on cruising for curb parking.
| ||Population regulation via feedback by Klahs, Phil and Karsai, Istvan
This simple model demonstrates the effect of feedback on birth and death to population growth.The model was inspired by Eigen and Winkler (1975) and analysed in detailed in Zsiros and Karsai (1997).
| ||Endocell by Barakah Quader
| ||GameTheory by Rick O'Gorman
"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. "
| ||BRADFORD WFF N Proof Quiz 7-4-14 by John Hamilton Bradford
Bradford proof quiz
| ||BRADFORD MINDING NORMS Hunting for Norms 7-1-14 by John Hamilton Bradford
Bradford minding norms
| ||BRADFORD Expectations Luhmann 6-26-14 by John Hamilton Bradford
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.htmlThe 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 ego's prior responses. EE refers to ego's expectation of alter's 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 alter's responses. Rather than basing one's 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 Sakodas Model of Social Interaction 6-25-14 by John Hamilton Bradford
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:
Patch_value = Sum (Vj / (Dj ^ (1/w))),
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.
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).
| ||Day and Night by Abhishek Bhatia
| ||Plant Community Dynamics by Lucas Kushner, Binney Girdler
Explore the joint effects of habitat fidelity and dispersal distance in a simple plant community
| ||Checkers by JiÅÃ LukÃ¡Å¡
Checkers model AI vs. AI for simulating game strategies.
| ||Extinction of Homo Economicus by Rolf Stenholm
A thought experiment to test Homo Economicus ability to survive natural selection.
| ||ARDERS by Klaus G. Troitzsch
The famous arders model
| ||Nanjing_CI_SIM_27_Nov_2013 by Helin Liu; Elisabete A. Silva
To examine the dynamics between the interaction of the development of creative industries and urban spatial structure
| ||BRADFORD PD PUBLIC GOODS GAME FULL 1-31-14 NETLOGO by John Hamilton Bradford
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 by John Hamilton Bradford
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 by Meghendra Singh
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 by Kaan
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 by Rolf Stenholm
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.
| ||MARS Migration by Jakob Virgil
a mars exo-migration model
| ||Opinion Diffusion in Congressional Committees by Maurice Champagne
This model is an adaptation to the homophily and opinion formation model by Michael Ms 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.
| ||NatSelGame by Michael Zito
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
| ||Information Cascades by Rob Carrington
This models studies the conditions under which information cascades can occur with signalling games between simple reinforcement learners.
| ||Bayes1D by Travis Monk
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.
| ||Drift by Travis Monk
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.
| ||Spatial by Travis Monk
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.
| ||OptionsMarketWithJumps by William Elliott
Stock Options market simulator making use of Geometric Brownian Motion, Jump Diffusion, and the Black Scholes equation.
| ||Kuhnian Paradigm Shift 2 by Jason Rines
This model was designed to look at Kuhnian Paradigm Shifts.
| ||PJ_TSP_heuristics_sep2013_V5 by Jose Costas
An ant colony optimization algorithm applied to the famous NP-hard TSP (travel salesperson problem).
| ||PJ_hungarian_v2 by jose costas
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.
| ||Modelo 1_3_6_5 by Computational Modelling Research Group
The Ricardian Model of International Trade.
| ||Social influence in networks by Michael Maes
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).
| ||Location Game by Jeff Russell
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.
| ||Schlieffen Logistics by Robert Allen, Brian Coffey, Dante Montgomery, Ashley Rawson, and Brian Stebar II
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).
| ||GraphingRationalFunctionsGame by Edwin Schasteen
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.
| ||Fracking_v13a by Horwitz
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
| ||PJ_Dijkstra by jose costas
Consider the following silly game to be played by a single person with an urn and as many white ballsand 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?".
| ||PJ_freddie by jose costas
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.
| ||Dados2 by Francisco Restivo
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
| ||Kelly by Francisco Restivo
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
| ||CoordinationAndSustainability by Klaus G. Troitzsch
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.
| ||Carbon Cycle by Systems&Cycles
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 by Systems&Cycles
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.
| ||Pond Macroscopic by Systems&Cycles
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.
| ||Pond Maicroscopic by Systems&Cycles
| ||EmptyBinCity by Christos Tzivanakis
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.
| ||MEGanE SysDyn Netlogo by Francisco Dieguez
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.
| ||Siste Mafia33, edited 2 by Adrian Ordemann and Benedito Faustinoni Neto.
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.
| ||RenKraut-SimulateOnlineCommunity by Yuqing Ren & Robert Kraut
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/
| ||LLNL by Michelle Saksena
| ||Educational Model of Speciation by Carter Merenstein
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.
| ||DiscreteLife5 by Van Parunak
An upgrade of the 2004 DiscreteLife (see below).
| ||PJ_Kelton4_10_queues by jose costas
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.
| ||MinimumWages by Klaus G. Troitzsch
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.
| ||Fisheries_and_Management_v3 by Stuart Kininmonth
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.
| ||OptionsMarket by William Elliott
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
| ||Smog by Madison Fitzpatrick
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.
| ||Growth_Used_in_Chapter_and_Distributed by Randall Boone
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.
| ||Peloton Simulation 3 by Hugh Trenchard
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.
| ||Phase Transition Noise by Unknown
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.
| ||Axelrod_Cultural_Dissemination by Arezky H. RodrÃguez
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).
| ||Jeopardy by Ali Saad
| ||DroneNET by The Soviet Unit
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.
| ||Kaboom by Ali Saad and Geoffrey Luu
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.
| ||Peloton 2 by Hugh Trenchard
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.
| ||Combustion of Methane by Stephen Fether
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.
| ||Solar Field Mapping 1p07 by Kenneth Schatten
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 .
| ||HNG by Manu MuÃ±oz Herrera
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)
| ||Lattice-Walking Turtles_15 by waleed M. Al-Adrousy
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
| ||FamiliarTrafficDiversion by Gary O'Brien
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.
| ||OSOSS1rc2 by David Wiley
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
| ||Robbery-with-qlearn by Amrutha
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.
| ||Peloton Dynamics by Hugh Trenchard
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.
| ||Girls Get Attached by YANG SHANSHAN
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.
| ||Immigrant, Leadership and Social change by Han shuyu
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.
| ||Pathological Gambling and Social Influence by Yeo Shu Hui
this models simulates the gambling behavior of pathological gamblers under the influence of other pathological gamblers and ex-gamblers.
| ||Smoker Behavior and Intimacy by Claudia Chong Pick Yee
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 by Ong Shu Fang
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.
| ||Occupational Stress Support by Tan Xin Yi
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.
| ||Positive & Negative Talk of Network by Cindy
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).
| ||PD N-Person with Strategies by Tan Yongzhi
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.
| ||Smoking motivation peer pressure by M.A. Helmich
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.
| ||Fashion-Models by Lau Wee Kiat
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.
| ||Fall-of-banks by Jose Angel Rodriguez
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.
| ||Evil Bunny Bully Model by Sean Kelly
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.
| ||Party Segregation by Asish Ghosh
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.
| ||Frogger Simple Reflect Agent by Mochamad Agung Tarecha
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 email@example.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.
| ||GBLCSA by
To use this model in its full form, please follow this link.
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.
| ||HOTnet by Marcello Tomasini
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.
| ||ClimateWise1_2 by Mike L Anderson
| ||FlockingColor_v5 by Norman Lee Johnson
Color Flocking Model with Group-size calculation and direction output.
| ||BEFERGYONET MODEL by Inocencio Rodriguez, Gerard DâSouza, Edward Rayburn and Tom Griggs
| ||FastMIS_from_1986 by Antonio Lo Russo and Carmelo Scarso
| ||FinalProj by Andy Wang
| ||Kiri test 2 by Kiri
This model demonstrates the pairing of guanine.
| ||PARASITERMINATOR_1 by Angel Criado
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 by Angel Criado
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.
| ||SpeciesWorld by Tony Lawson
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.
| ||Diffusion3 by Mallory Owen
This model looks at social strengthening, a hypothesis of how religious ritual behaviors can facilitate cumulative cultural evolution in humans.
| ||Improved Clonal Selection Algorithm for Solving Travelling Salesman Problem (v_4_1_3) by Adil Baykasoglu, Alper Saltabas, A. Serdar Tasan, Kemal Subulan
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.
| ||Hemangioblast Determination by Jerry Rhee
This is a heuristic model of mouse hemangioblast maturation at embryonic headfold stages.
| ||Bird's Eye by Shayryl Mae Ramos
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.
| ||Groupintegration_nobreededlinks by Martin C. Baker
Test upload of a class simulation.
| ||Kanban3_v5 by Mirko BlÃ¼ming
| ||Flocking with Predator by Janusz Strzepek
A model which builds on the Flocking Model by Uri Wilensky by adding a predator adversary.
| ||SolarSystemEnd by Toby Skinner
Death of Our Solar System
| ||Center of Mass v3 by Kent Wallace
This model is designed to allow students to explore how they think about Center of Mass.
| ||Haystacks by Jen Badham
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.
| ||NSS by Prashant Tiwari
| ||Agent-Based Model by Pradeep Kumar
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.
| ||Gravity (Final) - Ivaylo M by Ivaylo Madzharov
This is a planetary gravity simulator, or an orbital simulator. It simulates the orbitsof stellar bodies around each other depending on factors such as mass, speed, and distance. It also simulates collision between bodies.
| ||FriendshipGameRev_1_0_25 by David S. Dixon
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.
| ||Prisoner's dilemma by claudio by claudio augusto borges pavani
This is the prisoner's dilemma with up to six players and eight strategies.
| ||Post-earthquake activity by Mehdi Jalalpour|
This models simulates humans and traffic right after a given earthquake
| ||Solar Field Mapping 1p03 by Kenneth Schatten
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 .
| ||Classic Traveling Salesman by Wes Hileman
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.
| ||Feldman NetLogo Interface Algorithmic Finance by Todd Feldman
This is the basic version of a NetLogo model for financial markets.
| ||PERSECUTIONS by Luis Belmonte
A game of persecutions obsessives.
| ||Segundo jogo do conhecimento 2 by claudio augusto borges pavani
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 translatehelped by Antnio Carlos Barroso
| ||METAMORFOSIS by Luis Belmonte
This program illustrates the cycles of metamorphosis of frogs.
| ||CSS Generator by [InsertNameHere]<3
wip pretty much
| ||Modified random clusters method for landscape pattern simulation by James Millington|
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).
| ||MattnKim by Shelley Shin
| ||Agent-based N-person prisoner's dilemma by Michal Czaplinski
Evolving N-Person Prisoner's Dilemma
| ||Diabetes by Rodolfo Sanchez
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.
| ||Diabetes1 by Rodolfo Sanchez
Diabetes and glucose simulation
| ||3Economies by Romulus-Catalin Damaceanu
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.
| ||19Mai11 by Toumi Anis
Simulation d'embarquement des conteneurs sur un port
| ||MCLOUD-1 by M Iudin
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.
| ||BIGmodel by Tomas Rosival
| ||Relativity NG by Matthew Banks
| ||Light bike by Noah Thoron
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.
| ||1dCAexplorer by suslik
This is a 1 dimensional cellular automata explorer
| ||Jill's Ants by Jill Anderson
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.
| ||Neture by Uwe Grueters
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.
| ||EXPLORE VS EXPOLTE1 by Irshad Faisal
The Exploratron versus Exploitation Dilemma in InnovationThis 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 EXPOLTE by Irshad Faisal
The Exploratron versus Exploitation Dilemma in InnovationThis 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.
| ||SegregationExpanded by David Pugh
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).
| ||Anisakisim by Angel Criado
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.
| ||Babesim by Angel Criado
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.
| ||Brugiasim by Angel Criado
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.
| ||Cryptosporisim by Angel Criado
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.
| ||Egranulosim by Angel Criado
| ||Leishmanisim by Angel Criado
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.
| ||Plasmoknowlesim by Angel Criado
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.
| ||HnH by Max OrHai
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.
| ||Artillery by Eric Muhs
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.
| ||David Miller - Resteraunt Model by David Miller
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.
| ||Rhythm Simulator 2 by MJ Banks
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.
| ||Bandwagon 2D by Davide Secchi
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.
| ||Ants_AndrewE_add food3 by Andrew Erickson
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.
| ||CASM_Robot by Jaqueson Kingeski Galimberti
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 by WANG Chengjun
This model is created by WANG Chengjun,who focused on the simulation of the spiral of silence theory which is very extensive grand theory.
| ||AntTaskAlloc by Arvind Diggikar
| ||Silence spiral by Wang Chengjun
| ||HabitatFragmentation by George Kampis and Istvan Karsai
This model explores the stability of predator-prey ecosystems with fragmented habitats.
| ||CompExclusion by Andrew Yoak
| ||Vision Cone Example 2 by William John Teahan|
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 > Vision Cone Example.
| ||Vacuum Cleaner Robot by William John Teahan|
This model simulates a vacuum cleaner robot whose task is to clean the floor of a room
| ||Two States by William John Teahan|
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 by William John Teahan|
This model allows the user to fill in a Sudoku puzzle.
| ||Stick Figure Walking by William John Teahan|
This model provides a simple animation of a stick figure walking.
| ||Stick Figure Animation by William John Teahan|
Users of this model can create their own stick figure animations and save them as QuickTime movie files.
| ||State Machine Example 2 by William John Teahan|
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 > State Machine Example.
| ||Simple Walk by William John Teahan|
This model gets a turtle to execute some simple walking commands.
| ||Shuffle and Deal Cards by William John Teahan|
This model is an extension of the Shuffle Cards model that allows you to deal the cards as well.
| ||Shuffle Cards by William John Teahan|
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 by William John Teahan|
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 by William John Teahan|
This model applies standard search algorithms to the problem of searching mazes.
| ||Searching for Kevin Bacon 2 by William John Teahan|
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 by William John Teahan|
This model applies standard search algorithms to the problem of searching for a specific goal node in a network.
| ||Santa Fe Trail 2 by Loukas Georgiou and William John Teahan|
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 by William John Teahan|
This model is an attempt to recreate boids (see Craig Reynold's work) that employs basic obstacle avoidance steering behaviour.
| ||Obstacle Avoidance 1 by William John Teahan|
This model is an attempt to recreate boids (see Craig Reynold's work) that employs basic obstacle avoidance steering behaviour.
| ||NZ Birds by William John Teahan|
This model constructs and animates a decision tree for the problem of identifying New Zealand birds.
| ||Nested Triangles by William John Teahan|
This model shows how to use simple turtle drawing commands to draw some patterns made out of triangles.
| ||Nested Squares by William John Teahan|
This model shows how to draw squares six different ways.
| ||N Dimensional Space by William John Teahan|
This model visualises N dimensional data concerning New Zealand All Blacks.
| ||Missionaries and Cannibals by William John Teahan|
This model applies standard search algorithms to the classic search problem called Missionaries and Cannibals.
| ||Mazes-2 by William John Teahan|
This extends the Mazes model by adding the Butterfly Maze, and two further behaviours based on those from the Searching Mazes model.
| ||Mazes by William John Teahan|
This model shows how to get a simple reactive turtle agent to move around a maze.
| ||Map Drawing by William John Teahan|
Users can create their own maps using this model.
| ||Map and Image Annotator by William John Teahan|
Users can annotate maps and images using this NetLogo model.
| ||Manhattan Distance by William John Teahan|
This model illustrates the concept of Manhattan distance, and compares it to Euclidean distance.
| ||Look Ahead Example 2 by William John Teahan|
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 > Look Ahead Example.
| ||Load File by William John Teahan|
This model shows how to load text from a file.
| ||Line of Sight Example 2 by William John Teahan|
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 > Line of Sight Example.
| ||Life Example by William John Teahan|
This model shows how to use some simple commands in NetLogo to simulate the life cycle of people.
| ||Life Cycle Stages by William John Teahan|
This model shows an example of a finite state automata (FSA) that represents the life cycle stages of people throughout their lives.
| ||Language Modelling by William John Teahan|
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 by William John Teahan|
This model visualises the knowledge and reasoning processes for three toy problems using different methods for knowledge representation.
| ||Hill Climbing with Wall Following by William John Teahan|
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 by William John Teahan|
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 > Hill Climbing Example.
| ||Hampton Court Maze with Wall Following by William John Teahan|
This model gets a turtle to wander around the Hampton Court maze using wall following behaviour.
| ||Hampton Court Maze by William John Teahan|
This model draws a schematic representation of the Hampton Court Palace garden maze.
| ||Foxes and Rabbits 2 by William John Teahan|
This model creates foxes and rabbits. Once created, the rabbits move away from the foxes if they are too near.
| ||Foxes and Rabbits by William John Teahan|
This NetLogo model creates 100 foxes and 1000 rabbits.
| ||Communication T-T Example 2 by William John Teahan|
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 > Communication T-T Example.
| ||Follow Trail by William John Teahan|
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 by William John Teahan|
This model is an attempt to recreate boids (see Craig Reynold's work) that use seeking and fleeing steering behaviours.
| ||Flocking with Obstacles by William John Teahan|
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 > Flocking Example.
| ||Firebreak by William John Teahan|
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 by William John Teahan|
This model allows the user to calculate the entropy for a specific probability distribution.
| ||Empty Maze with Wall Following by William John Teahan|
This model gets a turtle to wander around the empty maze using wall following behaviour.
| ||Empty Maze by William John Teahan|
This model draws an empty maze with no inside walls.
| ||Crowd Path Following by William John Teahan|
This model is an attempt to recreate boids (see Craig Reynold's work) that use the crowd path following steering behaviour.
| ||Colour Cylinder by William John Teahan|
This model demonstrates how colour can be represented in 3 dimensions: hue, saturation and brightness.
| ||Chevening House Maze with Wall Following by William John Teahan|
This model gets a turtle to wander around the Chevening House maze using wall following behaviour.
| ||Chevening House Maze with Coloured Islands by William John Teahan|
This NetLogo model colours the islands in the Chevening House garden maze.
| ||Chevening House Maze by William John Teahan|
This model draws a schematic representation of the Chevening House garden maze.
| ||Chatbot by William John Teahan|
This model implements two basic chatbots - Liza and Harry - using regular expressions (via an extension to NetLogo).
| ||Central Park Events by William John Teahan|
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 by William John Teahan|
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 by William John Teahan|
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 by William John Teahan|
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 by William John Teahan|
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 by William John Teahan|
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 by William John Teahan|
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 > Wall Following Example. The purpose is to show how to implement a "Sense & Think & 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 by William John Teahan|
This model tries to visually simulate one possible solution to the problem of trying to get water to flow uphill.
| ||FinalProject by Joseph Khubelashvili and Patrick Bacon Blabler
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) by Qasim Siddique & Muhammad Hanzala Ali Abbass
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.
| ||Helper by aminul haque
| ||One_Stock_Systems by Marcus D. Gabriel
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.
| ||MaterialSim Grain Growth by
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/.
| ||Rubik3d by Desi Ariyadhi Suyamto & Aryo Adhi Condro
It is the 3D version of standard 3x3x3 rubik. Implemented in NetLogo by Desi Ariyadhi Suyamto and Aryo Adhi Condro. Dedicated for rubik cubers.
| ||Bacteria by Paul Hanson
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.
| ||Rubicism2 by Desi Suyamto
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.
| ||Quantum Life I by Carlos Pedro Gonçalves
This is a model of a Quantum Game of Life with path-dependent local quantum computation, exemplifying a Quantum Cellular Automaton.
| ||Santa Fe Ant Trail by Loukas Georgiou
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 by Nick Bennett
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.
| ||EditorDeRedes_0_2 by Francesc J. MIGUEL QUESADA
| ||Dissemination of Culture by Iain Weaver
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".
| ||Evacuation of a lecture hall by Alex Bromberger, Tobias Glaß
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.
| ||Angels and Mortals by Iain Weaver
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".
| ||Lake Victoria Complex System Study by Alexander Marlantes
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.
| ||Cooler Model by Annette Brickley
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 by Iain Weaver
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".
| ||Evolution by Iain Weaver
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 by Corey Nyako
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.
| ||Patch Tools by Talaya White
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
| ||Cornea patch formation by Jerry Rhee
This is a work-in-progress that seeks to understand how mosaic patches in mouse corneasarrange themselves into spirals. In part, it seeks to demonstrate the limitations of thecurrent "stem-cell model", which argues that the pattern results from preferentialplacement of stem cells at the periphery, coupled to centripetal migration. The yellowrepresents the parts of the mouse cornea that do not contain labeled clones, i.e., thereare cells there but they are not visible. The white ring around the periphery is thelimbus, a putative stem cell niche. The dark blue circles within the ring represent stemcells that serve as the sole provider of new "mosaic cells" (leaf shape, a representativecluster of ~16 cells) that ultimately migrate towards the center. Pacemaker cells have thesame shape but they are red and have independent adjustable controllers. The cells movebased on their ability to respond to a chemical that are secreted periodically by thepopulation. Their rhythm can be entrained but only during a window when they are notsecreting. The rules were inspired by coupled-oscillator and Dictyostelium literature.
| ||Growing peppers greenhouse by J.P.M. van Ruijven
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.
| ||Male_Heirs by Talaya White
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 by Aldo Martinez-Pinanez
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.pdfIn 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 firstname.lastname@example.org
| ||Helmets by Anna Klabunde
| ||Endogenous Export Modes by Pascal Bürki
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 by Cédric Sueur
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.
| ||Independence vs mimetism by Cédric Sueur
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 by Qasim Siddique
A Simple Game
| ||MyFlocking by Nacho Valladares
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.
| ||Malaria Control by Erin Flanagan
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 by Qasim Siddique
| ||OBS by Sifat Momen
This is a simple model that demonstrates how agents can avoid obstacles and find targets autonomously using the potential field approach.
| ||ForestFire3 by Qasim Siddique
A simulation of tree regrowth after a forest fire.
| ||SIMflucht_GIUB by Aben, P., Müller, J. Müller, T. Wagner, A.
| ||Flockingcolor by Norman Lee Johnson
| ||Meetingscheduling by Qasim Siddique
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.
| ||CopyingAndAssociating-2 by Derek A Rush
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.
| ||GarbageCan_buck by Guido Fioretti
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.
| ||GarbageCan_docker by Guido Fioretti
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.
| ||Fire Ecology by Ryan Kelly
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.
| ||Decay01 by lookang
This model simulates the spontaneous decay of a collection ofradioactive nuclei. As they decay and become stable, the plot of thenumber that are still radioactive demonstrates the notion of"half-life".
| ||Fire Simulation by Qasim Siddique
Fire Simulation for the system of EWAFF Early waring and altering systemfor forest fires
| ||Chess by Corey Haddad
A simple chess program. Not fully playble and many bugs but works as proof of concept.
| ||CellMusic-BrainMusic by Asymptote
This simulation creates music based on the patterns formed by the "Brian's Brain" cellular automaton.
| ||Andean_Networks by Luciano Stucchi
Este programa es el mdulo inicial de una serie de simulaciones que apuntan adescribir la manera en la cual se forman y sostienen las redes sociales en lascomunidades andinas, partiendo de las relaciones de intercambio yreciprocidad 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 generacuando en una poblacin de agentes con un requerimiento mnimo de energanecesario para sobrevivir (requirement) y una disponibilidad aleatoria de lamisma (production), se permite la creacin de links entre agentes, lo queconlleva a unintercambio de sus respectivas energas y por consiguiente, laposibilidad de que quienes no alcanzan el requerimiento mnimo, reciban(intercambien) energa de otros agentes y en promedio, se equilibren. ountlinks por crearse
| ||Redes_de_reciprocidad by MaríaJosé Bustamante
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.
| ||SearchResource by Romulus-Catalin Damaceanu
The agent-based computational algorithm used by turtle agent is based onWilensky  and gives to this the next improvements: (i) the algorithm has a variable number of searching directions incomparison 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 thesearching directions and the other is random and is used only if thefirst regime fails to find the resources that surrounds the agent.
| ||Sniffing space associations by Tim Ireland
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 . 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.
| ||Greenhouse Effect by Lisa Schultz
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.
| ||Hardy Weinberg Classroom Model by Kenneth Letendre
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.
| ||My own model - cooperative countries by Julia Verhoeven
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.
| ||Allostericenzymes by Nicolas Descostes
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.
| ||M3202-410-DesiSuyamto by Desi Ariyadhi Suyamto
| ||AxelrodV2 by MIchael Maes and Sergi Lozano
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.
| ||Planetary WeatherSim MultipleContinent by Asymptote
This model attempts to simulate weather patterns on a hypothetical planet, using variables such as humidity, precipitation and temperature.
| ||CostaPath by Derek Rush
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.
| ||Ants2 by ellen evers
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 by ellen evers
| ||Leaf-macro by Edmund Hazzard
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 by Edmund Hazzard
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".
| ||Segreg-vs-coord by sebastian Grauwin
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.
| ||Community Structure v_4 by David W. Rudge and William Merrow
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.
| ||Population Dynamics_v4 by David W. Rudge and William Merrow
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.
| ||MDR-model by Jason Bishai
This model explores the spread of multiple drug resistant TB through a population.
| ||LevelCrossing ver 2_1 by Ales JANOTA
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".
| ||The Bugs of Nyarlathotep by Andre Ourednik|
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 by Andre Ourednik|
This model combines Schellings spatial segregation model, Epstein&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 by Annette Brickley
This model illustrates the movement of carbon through the natural environment.
| ||Gottman 1 by Victor Wooddell
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.
| ||Colonialism by Desi Ariyadhi Suyamto
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.
| ||PedestriansV1 by Singhathip Mickaël
This model simulates what happens when people who move at different speeds interact when sharing finite space.
| ||CBNM-simu by Jun Wang
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.
| ||Grass by Grass growth
Simulates the growth of grass in relation to various environmental conditions.
| ||Marble-Fall-Icosystem-4 by Paolo Gaudiano
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 by Zhenjiang SHEN, Ping CHEN, Mitsuhiko KAWAKAMI
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 by Luís César da Costa , Marcelo Trindade dos Santos and Gilson Antônio Giraldi
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 asreleasing the signalling molecules, bacteria are also able to measure thenumber (concentration) of the molecules within a population. Nowadayswe use the term "Quorum Sensing" (QS) to describe the phenomenonwhereby the accumulation of signalling molecules enables a single cellto 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 allother bacteria. Presenting the model of cellular automata proposed todescribe the main mechanisms of Quorum Sensing where Vibrio & Fischeri,and its model using the concept of Multi-Agents System.
| ||Traffic_Simulation by Andrew Lansdowne|
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 by Derek Rush
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 by Thomas C. Jones
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).
| ||Photon_transmissivity_2 by Ted Wong
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.
| ||March by Elio Marchione
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.
| ||Miller by Elio Marchione
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.
| ||SimHeart by Asymptote
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 by Aaron Unger
A simple model of how sunlight, albedo, CO2 and clouds all work together to change the global earth temperature.
| ||Randomly_Walking by shashank singh
simple model of randomly walking , reproducing human population,
(a) with two sexes as usual (male female)
(b) implemented, through breed ;
(c) only females can reproduce,
(d) all agents eat food to live,(food is green , no food is brown),food regrows after some time
(e) all agents grow in size according to their age and after some threshold value die due to old age
(f) agents die due to food starvation too(g)females expend more energy in reproducing
| ||SSCrazyPingPong by Serg
My first model for NetLogo 3.1.4
| ||Mouse_Aorta_Initial_Model by Heather Hayenga
| ||Urbanization_MC by AndrÂ Ourednik & Pierre Dessemontet|
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 by Carlos Gershenson
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" , or Hiroki Sayama's "Swarm Chemistry" , with the advantage that you can play these with real people.
| ||Homework_highschool by Daniel Kuchta
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 by Ed Hazzard
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.
| ||Homo_Bellicus by Andrie Kraaij|
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...
| ||Evolutionary_Game_Theory_Big_Bird_Replicator_Dynamic by Jeff Russell
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 by Jeff Russell
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 by Ed Hazzard
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.
| ||Pathfinder by Robert Goldstone
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...
| ||Cluster by Lubrano Lavadera David Rosario
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 by KHOUADJIA Mustapha Redouane
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 by Baba Kofi Weusijana|
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.
| ||Gas_Distillation by George W. Dombi
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 by Abdiel E. Caceres-Gonzalez
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 by Zvi Vlodavsky. Doron Zarchy
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 by Ed Hazzard
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.
| ||Bug_Hunt_Evolution by Christopher J Whalen
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'.
| ||Epidemic_Typhoid_Fever_on_Disaster_Area by Agung Budi Sutiono, MD
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 by Mick Censored
An old arcade game called "Asteroid Belt."
| ||Big_Bang by David Bowen
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_Brownian_Motion by David Bowen
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.
| ||Gaslab_Two_Color_Gas by David Bowen
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 by David Bowen
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.
| ||Quantum_Financial_Market by Carlos Pedro Gonçalves
This is a evolutionary quantum game theoretical model of a financial market, introduced and tested empirically by C.P. Gonalves and C. Gonalves (2007).
| ||SickTown by Gordon McDonald
Studying the spread of infectious diseases in a small town environment.
| ||AntSystem by Christopher Roach
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.
| ||LogoMoth by Shawn Barr, Eric Charles, Owen Densmore, Stephen Guerin, & Nick Thompson
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.
| ||Bouncing_Ball by David McAvity
This simulation models the internal dynamics of a bouncing ball. Ordered energy becomes more and more disordered as the ball bounces.
| ||FractalMorph by David McAvity
Fractal morph is a NetLogo implementation of Richard Dawkins biomorphs. Users mimic evolution by selecting fractals from a fractal landscape.
| ||Vertical-Evacuation by Susanne Jul|
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.
| ||Example-HPP-3D by Luís César da Costa and James Steiner
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 by Sifat Momen
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 by Segismundo S. Izquierdo & Luis R. Izquierdo|
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.
| ||Recrystallization by Markus Kasim
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 by Cem D
Implementation based on Daniel B. Stouffer's MG implementation.
| ||Final_Preliminary_Model by Benjamin Roberts
This is my first Evacuation model with one exit, one agent wide
| ||Multi_Exit by Benjamin Roberts
This is my second modeling allowing for variation among number and size of exits
| ||Network_growth by Malik Koné
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.
| ||Obstruction_Model by Benjamin Roberts
This is my final model allowing for placing an obstruction or "barrior" in front of doorway causing agent organization.
| ||MG_cem_changed by Cem Dilmegani
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.
| ||Final Project by Matthew Colebeck
Here is a simulation that describes Newton's Second Law.
| ||Learning and Creativity by Derek A. Rush
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 by Luis R. Izquierdo|
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 by Desi Suyamto
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 by Amelie Zeng
This is Craps, the dice game (Without the gambling, of course.)
| ||Quicksort by pratik
No description given
| ||AdoptLearnOnLine by Desi Suyamto
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.
| ||MusiqueMulti-Agents by Hervé Provini
Modèle expérimental multi-agents pour la création musicale. Chaque agents a un comportement très simple. La mise en oeuvre d'une multitude d'agents et leurs interactions entre eux (et avec un signal entrant), donnent une émergence de forme musicale.
| ||GarbageCan by Guido Fioretti
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 by Luis Cesar da Costa
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 by David McAvity
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 by Gary An, MD
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 by Gary An, MD
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 by Gary An, MD
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.
| ||Reinforcement Learning Maze by Joe Roop
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.
| ||Reinforcement Learning Wargame by Joe Roop
This model implements Q-learning (Watkins 1989) a one-step temporal difference algorithm in the area of reinforcement learning.
| ||BirdAggression by Josh Rainwater
no description given
| ||2d_parity by hardik
no description given
| ||Asynchronous_Backtracking_-_binary_random_problems by Ionel Muscalagiu
This is the implementation of the Asynchronous Backtracking for the random binary problems
| ||Langtons_Ant_on_Infinite_Plane by Ivan Filippenko
no description submitted
| ||Good_Morning_Turtles_II by Michel Viacroze
"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 by Ionel Muscalagiu
"This is the implementation of the ABT kernel for the graph coloring problem."
| ||LevelCrossing by Ales Janota
Model of Level Crossing Operation.
| ||Level_Crossing by Ales Janota
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.
| ||Atomic-Force by Corey Haddad
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.
| ||Drivers' Behavior In Car Park by Umeyr Kureemun
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)
| ||CharityWorld-NL by Luis R. Izquierdo|
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.
| ||Fishery by Bill Silvert
A cellular automata model of the interaction between fishing boats and fish schools.
| ||drugsupply by Michael Agar, Stephen Guerin, Owen Densmore|
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.
| ||05_wegesys_attrakt by Reinhard Konig und Christian Bauriedel|
the spread particles flow to a defined point and leave trajectories.
| ||08_culturesFight09 by Reinhard Konig und Christian Bauriedel|
the behaviour-evolution of pixel cultures: cellular automata fighting about the given space.
| ||wegesystem04 by Reinhard Konig und Christian Bauriedel|
the model create a self-organizing path-system
| ||pestilence by Joe Glessner|
A disease spread simulation.
| ||Lorenz3D by Massimo Salzano
The Lorenz system is a well known example of a simple system showing chaos. Its dynamics depend on many parameters.
| ||OneDimensionalElection by Mary Lynn Reed
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.
| ||Emotion & Motivation by Derek A. Rush
Following upon two Netlogo models SELF-AWARENESS and IMAGINATION this model shows that a typical human relationship between EMOTION & MOTIVATION can be obtained with a simple iterative procedure and it extends the analysis to includePerception, Percepts, Memories, Display & Communication, to reach a conclusion about Consciousness.
| ||3d-cube-maze by James Steiner
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 by James Steiner
A 2D Maze generator and navigator, implemented in 3D.
| ||Shapefactory Model by Erik Johnston, Ning Nan, and Nathan Bos
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.
| ||Chemical Equilibrium elaborated by Russ Maurer
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.
| ||Asynchronous Backtracking-graphcoloring with flags by Ionel Muscalagiu
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.
| ||ABT kernel-graphcoloring-derived in Asynchronous Backtracking by Ionel Muscalagiu
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 by Ionel Muscalagiu
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"
| ||SOTL by Carlos Gershenson
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.
| ||LNmodel127-articleVersion by Rob Koper
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 by Ionel Muscalagiu
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 by Ionel Muscalagiu
This is the implementation of the ABT kernel - derived in Asynchronous Backtracking (Yokoo) with temporary links, for the graph coloring problem.
| ||ABT kernel-graphcoloring by Ionel Muscalagiu
This is the implementation of the ABT kernel for the graph coloring problem.
| ||AWCS with nogood processor centralized for the graph-coloring problem by Ionel Muscalagiu
This is the implementation of the Asynchronous Weak-Commitment Search with nogood processor for the graph coloring problem.
| ||Simulation de la recherche de nourriture par les fourmis (Ant Food Search Simulation) by Aurélien Saint Dizier|
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) by Aurélien Saint Dizier|
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) by Aurélien Saint Dizier|
An applet, in French, showing how a set of points "automatically" form a circle, if the parameters are correctly set
| ||NukeSnake by Jim Lyons
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.
| ||AWCS with the resolved-based learning for the graph-coloring problem by Ionel Muscalagiu
This is the implementation of the Asynchronous Weak-Commitment Search with the resolved-based learning for the graph coloring problem.
| ||lac operon by Steven Brewer|
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.
| ||Unknown Gene Expression by Steven Brewer|
This is a model that offers a series of "unknown" problems for students to explorein learning about gene expression systems.
| ||Logical Promoter by Steven Brewer|
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.
| ||ABTkernel by Ionel Muscalagiu
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."
| ||DisDBgraphcoloring by Ionel Muscalagiu
This solves the graph coloring problem using the Distributed Dynamic Backtracking algorithm from Christian Bessiere, Arnold Maestre, Pedro Meseguer.
| ||DisDBnqueens by Ionel Muscalagiu
This model solves the N-Queens problem using the Distributed Dynamic Backtracking algorithm from Christian Bessiere, Arnold Maestre, Pedro Meseguer.
| ||cruise by Owen Densmore|
This is a proof of concept for including GIS into NetLogo for a dynamic Car Cruising model within the Santa Fe downtown area.
| ||Bignum_Routines by Michael Kuyumcu
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.
| ||Drugtalk by Michael Agar
Drugtalk models how rates of use of an illicit drug result from user experiences and diffusion of those experiences through social and spatial networks.
| ||HIVSIM by Wilfred Ndifon
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.
| ||DrugPropagation by Robert Rohrkemper and Josh Savory
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.
| ||ProteinSynthesis by John Van Heukelem
Protein synthesis simulation.
| ||ElFarolBarProblem by Mark Garofalo
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.
| ||Innate Immune Response by Gary An
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.
| ||Binary Counter by Teresa Carrigan|
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.
| ||5 Short-term-memory-voters by Michael Kuyumcu
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.
| ||beergame by Owen Densmore|
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.
| ||Genetics and Cellular Automata by Theodore G. Wong|
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.
| ||Polygons by Luca Dentis
This is a very simple model that shows how to draw polygons using lists and sliders.
| ||DiscreteLife by Van Parunak
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.
| ||Lissajous by Paul Rieger
A simple model to draw Lissajous-figures.
| ||Court of the honeybee queen by Thomas Schmickl|
"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."
| ||layout by Owen Densmore|
"This is a dynamic graph layout model using springs and repulsion forces to create a pleasing layout."
| ||Artificial Financial Market by Carlos Pedro Gonçalves
"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."
| ||Building and Sorting by Thomas Schmickl|
"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)
| ||Herding by Carlos Pedro Gonçalves
"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."
| ||Predator-mediated coexistence by Felix Baerlocher
"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."
| ||Growth of Plants by Thomas Schmickl|
"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 by Thomas Schmickl|
"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 by Thomas Schmickl|
"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."
| ||Small World Tester by Stuart Astill|
"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."
| ||Flocking color by Norman L Johnson
"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."
| ||ARS-Genetics by Thomas Hills
"This is a genetic algorithm that evolves individual foragers capable of finding patches of red pixels."
| ||BinaryGA by Thomas Hills
"This is a more elementary genetic algorithm than the ARS, which has some fun properties."
| ||HopfieldLearning by Thomas Hills
"Here is a neural network (Binary Hopfield) that can identify pictures that you teach it."
| ||Contours & Sections by Derek Rush
"This model uses the terrain modelling of Netlogo Tutorial 3, (modified), to set up a terrain and then provides for contouring and sectioning."
| ||Queuing Systems by Jem Garnett|
"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."
| ||Buttons by Owen Densmore|
"This is a NetLogo model of the buttons phase transition presented in Stuart Kauffman's book At Home in the Universe."
| ||Spirals & Curve Matching by Derek Rush
"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 by Gianfranco Barone
"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 by Nigel Gilbert
"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). "
| ||EasyMoney by Derek Rush
"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 by Carlos Pedro Gonçalves
" This is a simulation of a model inspired in Per Bak's pile of sand... "
| ||Nonogram by Robert Holmes
"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 by Dylan Evans
"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 by Derek Rush
"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."
| ||Canal by Derek Rush
"This model illustrates the well known conundrum about the operation of the Panama Canal. "
| ||OilEdit by Suhaib
"Bioremediation of Oil Spills using hydrocarbon degrading bacteria."
| ||OptimismAISB2 by Dylan Evans
"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. "
| ||MagnetFun by Jerry James
"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 by Jerry James
"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..."
| ||Logistic by Carlos Pedro Gonçalves
"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..."
| ||Imagination by Derek Rush
"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..."
| ||Ant Space by Tim Brown|
"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 by Owen Densmore|
"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 by Peter Donovan|
"This is a simple pasture management or grazing model..."
| ||Hillwalker by Derek Rush
"HILLWALKER is a model inspired by the Tutorial Model 3 and it uses the random terrain creating code of that model, but modified..."
| ||INDIAN by michelle
| ||Gliders by Brian Prentice|
"Demonstrates that gliders with arbitrary speed and direction can be supported with a simple cellular automata program..."
| ||Self-awareness by Derek Rush
"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 by Nigel Gilbert
"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. "
| ||Popeq by Derek Rush
"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. "
| ||AntsOpt by Erich Neuwirth
"In this model ants try to find a short path from the left upper corner to the right lower corner of the area."