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The effects of attribute persistence on cooperation in evolutionary games

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  • Yang, Kai
  • Huang, Changwei
  • Dai, Qionglin
  • Yang, Junzhong

Abstract

In ordinary evolutionary game theory, players update their strategies according to a certain payoff-driven rule. Szolnoki and Perc (2015) [44] found conformity-enhanced network reciprocity by introducing conformity-driven strategy-updating rule to an appropriate fraction of players. In this work, we treat strategy-updating rule as an attribute of players and allow for the evolution of the attribute, for example, the alternation of the strategy-updating rule between payoff-driven and conformity-driven rules with time. We introduce the persistence parameter T by assuming that players change their strategy-updating rules every T Monte Carlo time unit according to either unbiased rule or aspiration rule. We find that frequent alternation of strategy-updating rule improves the conformity-enhanced network reciprocity for the unbiased rule, which leads that small T greatly promotes cooperation. On the other hand, we find no improvement of conformity-enhanced network reciprocity for the aspiration rule.

Suggested Citation

  • Yang, Kai & Huang, Changwei & Dai, Qionglin & Yang, Junzhong, 2018. "The effects of attribute persistence on cooperation in evolutionary games," Chaos, Solitons & Fractals, Elsevier, vol. 115(C), pages 23-28.
    • Handle: RePEc:eee:chsofr:v:115:y:2018:i:c:p:23-28
    DOI: 10.1016/j.chaos.2018.08.018
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    Cited by:

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    2. Zhang, Liming & Huang, Changwei & Li, Haihong & Dai, Qionglin & Yang, Junzhong, 2021. "Cooperation guided by imitation, aspiration and conformity-driven dynamics in evolutionary games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 561(C).
    3. Liu, Danna & Huang, Changwei & Dai, Qionglin & Li, Haihong, 2019. "Positive correlation between strategy persistence and teaching ability promotes cooperation in evolutionary Prisoner’s Dilemma games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 267-274.
    4. Zhao, Yakun & Xiong, Tianyu & Zheng, Lei & Li, Yumeng & Chen, Xiaojie, 2020. "The effect of similarity on the evolution of fairness in the ultimatum game," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).
    5. Han, Xu & Zhao, Xiaowei & Xia, Haoxiang, 2022. "Hybrid learning promotes cooperation in the spatial prisoner’s dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    6. Lin, Jingyan & Huang, Changwei & Dai, Qionglin & Yang, Junzhong, 2020. "Evolutionary game dynamics of combining the payoff-driven and conformity-driven update rules," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    7. Quan, Ji & Dong, Xu & Wang, Xianjia, 2022. "Rational conformity behavior in social learning promotes cooperation in spatial public goods game," Applied Mathematics and Computation, Elsevier, vol. 425(C).
    8. Zhu, Yuying & Xia, Chengyi, 2023. "Asynchronous best-response dynamics of networked anti-coordination game with payoff incentives," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).

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