Self-Propelled Agents and Group Social Force
Peng Wang, Peter Luh

TL;DR
This paper explores a model of self-propelled agents with social interaction forces to understand collective decision-making and social dynamics, emphasizing binary choices and agent interactions in social networks.
Contribution
It introduces a quantitative framework for social relationship arrays and group social forces in self-propelled agent models for social and economic phenomena.
Findings
Model captures collective decision processes with discrete choices.
Agent interactions influence social movement and self-organization.
Simulation reflects complex social behaviors and de-individualization effects.
Abstract
Brownian motion have long been studied on a diversity of fields, not only in physics of statistical mechanics, but also in biological models, finance and economic process, and social systems. In the past twenty years, there has been a growing interest in studying the model in self-propelled feature and interaction force such that the model also fits into study of social phenomenon of many individuals. This article will continue with this research trend and especially investigate the model in paradigms for a quantitative description of social and economic process. We mainly discuss a class of collective decision process of Brownian agent/particles, where the stochastic process does not exist in the fluctuation in the traditional Brownian motion, but in selection among several discrete choices. Their decisions interacts with each other in a given social topology. To simplify our…
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Taxonomy
TopicsEvolutionary Game Theory and Cooperation
