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Reputation-based asymmetric comparison of fitness promotes cooperation on complex networks

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  • Zhang, Zhipeng
  • Wu, Yu’e
  • Zhang, Shuhua

Abstract

Reputation is elaborated in society and has a great effect on individual fitness, under which each player acquires a special fitness. An asymmetric comparison will appear when players update their strategies based on fitness and imitation dynamics. To explore the impact of the above asymmetry on the evolution of cooperation, we present a new strategy updating rule. More precisely, a player compares his/her own fitness with neighbor’s payoff when he/she updates strategy. In this paper, individual payoff is dependent on both his/her strategy and partner’s strategy; and individual fitness is calculated according to individual payoff and reputation value. Extensive simulation results illustrate that in spatial evolutionary prisoner’s dilemma game, with the help of this new strategy updating rule, the proportion of cooperators increases significantly within a wide range of parameter value. During the evolution of cooperation, asymmetric comparison of fitness can enhance network reciprocity effectively. Furthermore, a discussion on micro dynamics from the perspective of fitness is presented. To test the generality of this mechanism, we also use this new updating rule to simulate the evolution of spatial snowdrift game. In addition, the results obtained on Barabási–Albert Scale-Free network and Erdős–Rényi random graph are also shown. Our work helps to understand the evolution of cooperation and reputation.

Suggested Citation

  • Zhang, Zhipeng & Wu, Yu’e & Zhang, Shuhua, 2022. "Reputation-based asymmetric comparison of fitness promotes cooperation on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    • Handle: RePEc:eee:phsmap:v:608:y:2022:i:p1:s0378437122008263
    DOI: 10.1016/j.physa.2022.128268
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    References listed on IDEAS

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