Adaptive interaction driven by the learning effect in the spatial prisoner's dilemma  

作　　者：李佳奇 张建磊 刘群 Jiaqi Li;Jianlei Zhang;Qun Liu(Institute of Intelligent Information,Hexi University,Gansu 734000,China;College of Artificial Intelligence,Nankai University,Tianjin 300350,China)

机构地区：[1]Institute of Intelligent Information,Hexi University,Gansu 734000,China [2]College of Artificial Intelligence,Nankai University,Tianjin 300350,China

出　　处：《Chinese Physics B》2024年第3期160-169,共10页中国物理B（英文版）

基　　金：Project supported by the National Natural Science Foundation of China(Grant No.61963013).

摘　　要：We propose a computing model in which individuals can automatically adjust their interaction intensity with their mentor according to the learning effect.This model is designed to investigate the cooperative dynamics of the spatial prisoner's dilemma.More specifically,when the cumulative payoff of a learner is more than his reference earning,he will strengthen his interaction with his mentor;otherwise,he will reduce it.The experimental results indicate that this mechanism can improve the emergence of cooperation in a networked population and that the driving coefficient of interaction intensity plays an important role in promoting cooperation.Interestingly,under a certain social dilemma condition,there exists a minimal driving coefficient that leads to optimal cooperation.This occurs due to a positive feedback effect between the individual's satisfaction frequency and the number of effective neighbors.Moreover,we find that the experimental results are in accord with theoretical predictions obtained from an extension of the classical pair-approximation method.Our conclusions obtained by considering relationships with mentors can provide a new perspective for future investigations into the dynamics of evolutionary games within structured populations.

关 键 词：self-adapting interaction evolutionary game MENTOR spatial prisoner's dilemma 

分 类 号：O225[理学—运筹学与控制论]