基于行为惩罚的合作演化研究  

Research on Evolution of Cooperation Based on Behavioral Punishment

作　　者：裴华艳 闫光辉[1] 王焕民[2] PEI Hua-yan;YAN Guang-hui;WANG Huan-min(School of Electronic and Information Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China;Mechatronics T&R Institute,Lanzhou Jiaotong University,Lanzhou 730070,China)

机构地区：[1]兰州交通大学电子与信息工程学院,兰州730070 [2]兰州交通大学机电技术研究所,兰州730070

出　　处：《兰州交通大学学报》2020年第2期71-75,共5页Journal of Lanzhou Jiaotong University

摘　　要：针对复杂网络演化博弈中合作的产生与演化,基于二人重复囚徒困境博弈提出了一种基于行为惩罚的博弈策略与网络拓扑结构共演化模型,重点研究了行为惩罚机制对个体策略行为与群体合作水平的影响.在规则小世界网络上验证了该模型.仿真结果表明:行为惩罚能够促进个体合作行为的产生,显著提升群体的合作水平;当系统到达演化稳定状态时,演化产生的小世界网络呈现出异质性与异配性特征,进一步促进了合作行为的演化;网络拓扑结构更新时间尺度的增长促进了更高水平合作的产生.In order to investigate the emergence and evolution of cooperation in the evolutionary games of complex networks,a behavioral punishment based co-evolutionary model of game strategy and network topology is proposed based on the two-strategy repeated prisoner’s dilemma game.The study mainly focuses on the effect of the behavioral punishment mechanism on individuals’strategy behavior and average cooperation level in the population.Simulations is carried in a regular small-world network.Results show that the behavioral punishment can promote the emergence of individuals’cooperative behaviors and significantly advance the cooperation in the population.Furthermore,the evolved small-world network presents heterogeneity and disassortativity after the system has reached a stationary state,which further promote the evolution of cooperation.Additionally,further increase of network topology updating time scale facilitates the emergence of higher level of cooperation.

关 键 词：演化博弈理论 合作演化 行为惩罚 囚徒困境博弈 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]