Resolution of the Stochastic Strategy Spatial Prisoner&apos;s Dilemma by   Means of Particle Swarm Optimization

doi:10.1371/journal.pone.0021787

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	Resolution of the Stochastic Strategy Spatial Prisoner's Dilemma by Means of Particle Swarm Optimization
	Zhang, Jianlei ; Zhang, Chunyan ; Chu, Tianguang ; Perc, Matjaz
刊名	plos one
	2011
关键词	INDIRECT RECIPROCITY EVOLUTIONARY GAMES COMPLEX NETWORKS SOCIAL DILEMMAS SNOWDRIFT GAME COOPERATION SELECTION INDIVIDUALS POPULATIONS DYNAMICS
DOI	10.1371/journal.pone.0021787
英文摘要	We study the evolution of cooperation among selfish individuals in the stochastic strategy spatial prisoner's dilemma game. We equip players with the particle swarm optimization technique, and find that it may lead to highly cooperative states even if the temptations to defect are strong. The concept of particle swarm optimization was originally introduced within a simple model of social dynamics that can describe the formation of a swarm, i.e., analogous to a swarm of bees searching for a food source. Essentially, particle swarm optimization foresees changes in the velocity profile of each player, such that the best locations are targeted and eventually occupied. In our case, each player keeps track of the highest payoff attained within a local topological neighborhood and its individual highest payoff. Thus, players make use of their own memory that keeps score of the most profitable strategy in previous actions, as well as use of the knowledge gained by the swarm as a whole, to find the best available strategy for themselves and the society. Following extensive simulations of this setup, we find a significant increase in the level of cooperation for a wide range of parameters, and also a full resolution of the prisoner's dilemma. We also demonstrate extreme efficiency of the optimization algorithm when dealing with environments that strongly favor the proliferation of defection, which in turn suggests that swarming could be an important phenomenon by means of which cooperation can be sustained even under highly unfavorable conditions. We thus present an alternative way of understanding the evolution of cooperative behavior and its ubiquitous presence in nature, and we hope that this study will be inspirational for future efforts aimed in this direction.; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000292655400019&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Multidisciplinary Sciences; SCI(E); PubMed; 17; ARTICLE; 7; e21787; 6
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/315691]
专题	工学院
推荐引用方式 GB/T 7714	Zhang, Jianlei,Zhang, Chunyan,Chu, Tianguang,et al. Resolution of the Stochastic Strategy Spatial Prisoner's Dilemma by Means of Particle Swarm Optimization[J]. plos one,2011.
APA	Zhang, Jianlei,Zhang, Chunyan,Chu, Tianguang,&Perc, Matjaz.(2011).Resolution of the Stochastic Strategy Spatial Prisoner's Dilemma by Means of Particle Swarm Optimization.plos one.
MLA	Zhang, Jianlei,et al."Resolution of the Stochastic Strategy Spatial Prisoner's Dilemma by Means of Particle Swarm Optimization".plos one (2011).