文章基本信息

标题：PSO Algorithm for IPD Game
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作者：Xiaoyang Wang ; Yibin Lin
期刊名称：International Journal of Computer Science & Information Technology (IJCSIT)
印刷版ISSN：0975-4660
电子版ISSN：0975-3826
出版年度：2012
卷号：4
期号：4
页码：23
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Mechanisms promoting the evolution of cooperation in two-player, two-strategy evolutionary games havebeen discussed in great detail over the past decades. Understanding the effects of repeated interactions inmulti-player with multi-choice is a formidable challenge. This paper presents and investigates theapplication of co-evolutionary training techniques based on particle swarm optimization (PSO) to evolvecooperation for the iterated prisoner’s dilemma (IPD) game with multiple choices in noisy environment.Several issues will be addressed, which include the evolution of cooperation and the evolutionary stabilityin the presence of multiple choices and noise. First is using PSO approach to evolve cooperation. Thesecond is the impact of noise on the evolution of cooperation is examined
关键词：co-evolution; iterated prisoner’s dilemma (IPD); particle swarm optimization (PSO); social component;noise