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Aspiration drives adaptive switching between two different payoff matrices

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  • Li, Jiaqi
  • Zhang, Jianlei
  • Chen, Zengqiang
  • Liu, Qun

Abstract

Under given social dilemma, different individuals perhaps have different perceptions for the dilemma intensity. Generally speaking, the degree of individual’s perception should be closely related to its ability, the stronger the ability of individual, the weaker the perception for the dilemma intensity will be. On the other hand, the competent individuals may be more likely to carry out altruistic cooperation behavior than those who are relatively lacking in ability. Considering these facts, we introduce an evolutionary game model in which individual can adaptively switch between two payoff matrices with different temptations based on aspiration to explore the cooperation dynamics in spatial prisoner’s dilemma. In this model, two different payoff matrices are denoted by Mw and Ms respectively, the temptation value of the former is small, and the one of the latter is large. For the individual who has adopted Mw to interact, the higher the individual is satisfied with the current payoff, the lower the probability of switching to Ms in the next round, while for the individual who has adopted Ms to interact, the higher the individual is satisfied with the current payoff, the higher the probability of switching to Mw in the next round. Experimental results show that this mechanism of adaptive switching between payoff matrices with different temptations can effectively promote the cooperation of spatial prisoner’s dilemma, and the appropriate aspiration level of individual can provide the most favorable environment for the diffusion of cooperation. The difference in the perception for dilemma intensity will be a new perspective in the study of networked evolution game.

Suggested Citation

  • Li, Jiaqi & Zhang, Jianlei & Chen, Zengqiang & Liu, Qun, 2023. "Aspiration drives adaptive switching between two different payoff matrices," Applied Mathematics and Computation, Elsevier, vol. 446(C).
    • Handle: RePEc:eee:apmaco:v:446:y:2023:i:c:s0096300323000504
    DOI: 10.1016/j.amc.2023.127881
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    References listed on IDEAS

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    1. Li, Jiaqi & Zhang, Jianlei & Liu, Qun, 2024. "Spatial game with multiple interaction patterns in constrained interaction environment: A computational method based on opponent’s ability," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).

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