Beginners Interactive NetLogo Dictionary (BIND)
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NetLogo Models Library:
If you download the NetLogo application, this model is included. You can also Try running it in NetLogo Web
This model, due to Robert Axelrod and Ross A. Hammond, suggests that "ethnocentric" behavior can evolve under a wide variety of conditions, even when there are no native "ethnocentrics" and no way to differentiate between agent types. Agents compete for limited space via Prisoner Dilemma's type interactions. "Ethnocentric" agents treat agents within their group more beneficially than those outside their group. The model includes a mechanism for inheritance (genetic or cultural) of strategies.
Each agent has three traits: a) color, b) whether they cooperate with same colored agents, and c) whether they cooperate with different colored agents. An "ethnocentric" agent is one which cooperates with same colored agents, but does not cooperate with different colored agents. An "altruist" cooperates with all agents, while an "egoist" cooperates with no one. A "cosmopolitan" cooperates with agents of a different color but not of their own color.
At each time step, the following events occur:
Up to IMMIGRANTS-PER-DAY, new agents appear in random locations with random traits.
Agents start with an INITIAL-PTR (Potential-To-Reproduce) chance of reproducing. Each pair of adjacent agents interact in a one-move Prisoner's Dilemma in which each chooses whether or not to help the other. They either gain, or lose some of their potential to reproduce.
In random order, each agent is given a chance to reproduce. Offspring have the same traits as their parents, with a MUTATION-RATE chance of each trait mutating. Agents are only allowed to reproduce if there is an empty space next to them. Each agent's birth-rate is reset to the INITIAL-PTR.
The agent has a DEATH-RATE chance of dying, making room for future offspring and immigrants.
To prepare the simulation for a new run, press SETUP EMPTY. Press GO to start the simulation running, press GO again to stop it.
SETUP FULL will allow you to start with a full world of random agents.
COST-OF-GIVING indicates how much it costs an agent to cooperate with another agent.
GAIN-OF-RECEIVING indicates how much an agent gains if another agent cooperates with them.
IMMIGRANT-CHANCE-COOPERATE-WITH-SAME indicates the probability that an immigrating agent will have the COOPERATE-WITH-SAME? variable set to true.
IMMIGRANT-CHANCE-COOPERATE-WITH-DIFFERENT indicates the probability that an immigrating agent will have the COOPERATE-WITH-DIFFERENT? variable set to true.
The STRATEGY COUNTS plot tracks the number of agents that utilize a given cooperation strategy:
CC --- People who cooperate with everyone CD --- People who cooperate only with people of the same type DD --- People who do not cooperate with anyone DC --- People who only cooperate with people of different types
Agents appear as circles if they cooperate with the same color. They are filled in if they also cooperate with a different color (altruists) or empty if they do not (ethnocentrics). Agents are squares if they do not cooperate with the same color. The agents are filled in if they cooperate with a different color (cosmopolitans) or empty if they do not (egoists).
Observe the interaction along the edge of a group of ethnocentric agents, and non-ethnocentric agents. What behaviors do you see? Is one more stable? Does one expand into the other group?
Observer the STRATEGY COUNTS plot. Does one strategy occur more than others? What happens when we change the model?
Set the IMMIGRANT-CHANCE-COOPERATE sliders both to 1.0. This means there are only altruists created. Do ethnocentrics and other strategies ever evolve? Do they ever out compete the altruists?
Change the values of COST-OF-GIVING and GAIN-OF-RECEIVING and observe the effects on the model and the level of ethnocentricity.
This model comes with a group of BehaviorSpace experiments defined. You can access them by choosing BehaviorSpace on the Tools menu. These are the original experiments that Axelrod and Hammond ran to test the robustness of this model. These experiments vary lots of parameters like the size of the world, IMMIGRANTS-PER-DAY and COST-OF-GIVING. These experiments are detailed at http://www-personal.umich.edu/~axe/Shared_Files/Axelrod.Hammond/index.htm
Add more colors to the model. Does the behavior change?
Make some patches richer than others, so that agents on them have a higher chance of reproducing. Distribute this advantage across the world in different ways such as randomly, in blobs, or in quarters.
Tag patches with a color. distribute the colors across the world in different ways: blobs, randomly, in discrete quarters. Agents use the patch color under other agents to determine whether to cooperate with them or not.
To ensure fairness, the agents should run in random order. Agentsets in NetLogo are always in random order, so no extra code is needed to achieve this.
This model is a NetLogo version of the ethnocentrism model presented by Robert Axelrod at Northwestern University at the NICO (Northwestern Institute on Complex Systems) conference on October 25th, 2003.
See also Ross A. Hammond and Robert Axelrod, The Evolution of Ethnocentrism, http://www-personal.umich.edu/~axe/research/AxHamm_Ethno.pdf
If you mention this model or the NetLogo software in a publication, we ask that you include the citations below.
For the model itself:
Please cite the NetLogo software as:
Copyright 2003 Uri Wilensky.
This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-sa/3.0/ or send a letter to Creative Commons, 559 Nathan Abbott Way, Stanford, California 94305, USA.
Commercial licenses are also available. To inquire about commercial licenses, please contact Uri Wilensky at email@example.com.
This model was created as part of the projects: PARTICIPATORY SIMULATIONS: NETWORK-BASED DESIGN FOR SYSTEMS LEARNING IN CLASSROOMS and/or INTEGRATED SIMULATION AND MODELING ENVIRONMENT. The project gratefully acknowledges the support of the National Science Foundation (REPP & ROLE programs) -- grant numbers REC #9814682 and REC-0126227.
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