Computational models of collective behavior

by: Robert L Goldstone, Marco A Janssen

Trends in Cognitive Sciences, Vol. 9, No. 9. (September 2005), pp. 424-430.

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Abstract

Computational models of human collective behavior offer promise in providing quantitative and empirically verifiable accounts of how individual decisions lead to the emergence of group-level organizations. Agent-based models (ABMs) describe interactions among individual agents and their environment, and provide a process-oriented alternative to descriptive mathematical models. Recent ABMs provide compelling accounts of group pattern formation, contagion and cooperation, and can be used to predict, manipulate and improve upon collective behavior. ABMs overcome an assumption that underlies much of cognitive science - that the individual is the crucial unit of cognition. The alternative advocated here is that individuals participate in collective organizations that they might not understand or even perceive, and that these organizations affect and are affected by individual behavior.

@article{citeulike:306015, abstract = {Computational models of human collective behavior offer promise in providing quantitative and empirically verifiable accounts of how individual decisions lead to the emergence of group-level organizations. Agent-based models (ABMs) describe interactions among individual agents and their environment, and provide a process-oriented alternative to descriptive mathematical models. Recent ABMs provide compelling accounts of group pattern formation, contagion and cooperation, and can be used to predict, manipulate and improve upon collective behavior. ABMs overcome an assumption that underlies much of cognitive science - that the individual is the crucial unit of cognition. The alternative advocated here is that individuals participate in collective organizations that they might not understand or even perceive, and that these organizations affect and are affected by individual behavior.}, author = {Goldstone, Robert L. and Janssen, Marco A. }, citeulike-article-id = {306015}, doi = {http://dx.doi.org/10.1016/j.tics.2005.07.009}, journal = {Trends in Cognitive Sciences}, keywords = {agents, collective-behavior, emergence}, month = {September}, number = {9}, pages = {424--430}, posted-at = {2005-08-29 11:04:48}, priority = {4}, title = {Computational models of collective behavior}, url = {http://dx.doi.org/10.1016/j.tics.2005.07.009}, volume = {9}, year = {2005} }

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TY - JOUR ID - citeulike:306015 L3 - citeulike-article-id:306015 TI - Computational models of collective behavior JF - Trends in Cognitive Sciences VL - 9 IS - 9 SP - 424 EP - 430 N2 - Computational models of human collective behavior offer promise in providing quantitative and empirically verifiable accounts of how individual decisions lead to the emergence of group-level organizations. Agent-based models (ABMs) describe interactions among individual agents and their environment, and provide a process-oriented alternative to descriptive mathematical models. Recent ABMs provide compelling accounts of group pattern formation, contagion and cooperation, and can be used to predict, manipulate and improve upon collective behavior. ABMs overcome an assumption that underlies much of cognitive science - that the individual is the crucial unit of cognition. The alternative advocated here is that individuals participate in collective organizations that they might not understand or even perceive, and that these organizations affect and are affected by individual behavior. KW - agents KW - collective-behavior KW - emergence AU - Goldstone, Robert AU - Janssen, Marco PY - 2005/09// UR - http://dx.doi.org/10.1016/j.tics.2005.07.009 ER -

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