THE EFFECT OF A HISTORY-FITNESS-BASED UPDATING RULE ON EVOLUTIONARY GAMES

Wen-Bo Du (), Xian-Bin Cao (), Run-Ran Liu () and Chun-Xiao Jia
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Wen-Bo Du: School of Electronic and Information Engineering, Beihang University, Beijing 100083, P. R. China;
Xian-Bin Cao: School of Electronic and Information Engineering, Beihang University, Beijing 100083, P. R. China
Run-Ran Liu: Department of Modern Physics, University of Science and Technology of China, Hefei, Anhui 230026, P. R. China
Chun-Xiao Jia: Department of Modern Physics, University of Science and Technology of China, Hefei, Anhui 230026, P. R. China

International Journal of Modern Physics C (IJMPC), 2010, vol. 21, issue 12, 1433-1442

Abstract: In this paper, we introduce a history-fitness-based updating rule into the evolutionary prisoner's dilemma game (PDG) on square lattices, and study how it works on the evolution of cooperation level. Under this updating rule, the playeriwill firstly select playerjfrom its direct neighbors at random and then compare their fitness which is determined by the current payoff and history fitness. If playeri's fitness is larger than that ofj, playeriwill be more likely to keep its own strategy. Numerical results show that the cooperation level is remarkably promoted by the history-fitness-based updating rule. Moreover, there exists a moderate mixing proportion of current payoff and history fitness that can induce the optimal fitness, where the highest cooperation level is obtained. Our work may shed some new light on the ubiquitous cooperative behaviors in nature and society induced by the history factor.

Keywords: Evolutionary game; cooperation; networks; history fitness; 87.23.Kg; 02.50.Le; 87.23.Ge; 89.65.-s; 89.75.Fb (search for similar items in EconPapers)
Date: 2010
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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DOI: 10.1142/S0129183110015956

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