基于Agent的演化博弈下的合作行为研究

文章在演化博弈的视角下，利用重复囚徒困境博弈（IPD）对合作的演化进行分析。在平均场假设下，合作策略无法在竞争中生存。而在基于Agent的演化博弈中，合作策略有可能获得成功。其原因在于通过限制合作行为的范围，可以使合作者聚集成簇状，从而防止合作的红利被背叛者占有。通过理论推导与计算机仿真，文章证明了利他策略获得成功的条件是c/b/1/m，并对此结果做出了解释。

Cooperation under Agent-based Evolutionary Games

〔Abstract〕 This article used IPD to analyze the evolution of cooperative behavior in the field of evolutionary game theory . Under the mean-field assumption , cooperator cannot survive in competition with defectors . However , in agent -based evolutionary game theory , cooperators can thrive . The reason for that is by restricting the scope of cooperation , cooperators can survive by living in clusters , thereby preventing the benefit of cooperation from being exploited by defectors . This article not only compares the difference between spatial evolu-tionary theory and classical theory , but also analyzes the conditions needed for the emergence and maintenance of cooperation using PD game simulation on a regular network .