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

作者机构：Institute of Intelligent InformationHexi UniversityGansu 734000China College of Artificial IntelligenceNankai UniversityTianjin 300350China 

出 版 物：《Chinese Physics B》 (中国物理B（英文版）)

年 卷 期：2024年第33卷第3期

页      面：160-169页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070105[理学-运筹学与控制论] 0701[理学-数学] 0702[理学-物理学] 

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

主　　题：self-adapting interaction evolutionary game mentor spatial prisoner's dilemma 

摘      要：We propose a computing model in which individuals can automatically adjust their interaction intensity with their mentor according to the learning *** model is designed to investigate the cooperative dynamics of the spatial prisoner s *** 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 *** 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 ***,under a certain social dilemma condition,there exists a minimal driving coefficient that leads to optimal *** occurs due to a positive feedback effect between the individual s satisfaction frequency and the number of effective ***,we find that the experimental results are in accord with theoretical predictions obtained from an extension of the classical pair-approximation *** conclusions obtained by considering relationships with mentors can provide a new perspective for future investigations into the dynamics of evolutionary games within structured populations.