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Proper aspiration level promotes generous behavior in the spatial prisoner’s dilemma game

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  • Zhi-Hai Rong

    (CompleX Lab, Web Sciences Center, University of Electronic Science and Technology of China
    The Hong Kong Polytechnic University)

  • Qian Zhao

    (CompleX Lab, Web Sciences Center, University of Electronic Science and Technology of China)

  • Zhi-Xi Wu

    (Institute of Computational Physics and Complex Systems, Lanzhou University)

  • Tao Zhou

    (CompleX Lab, Web Sciences Center, University of Electronic Science and Technology of China
    Big Data Research Center, University of Electronic Science and Technology of China)

  • Chi Kong Tse

    (The Hong Kong Polytechnic University)

Abstract

Zero-determinant strategies, which can unilaterally define a linear relationship between two individuals’ long-term payoff, have drawn much attention to comprehend the emergence of cooperation among individuals with repeated interactions. A subset of zero-determinant strategies, extortion strategy, can let an extortioner’s surplus exceed her opponent’s by a fixed percentage. On the other hand, the dual generosity strategy can ensure that a complier’s payoff is never larger than her opponent’s. In the framework of the prisoner’s dilemma game driven by payoff aspiration, we investigate in this paper the evolution of generosity strategy, in competition with extortion and unconditional defection strategies. We show that extortioners act as a catalyst to induce more defectors to change to compliers. Such influence will enhance when extortioners become more greedy. At a low aspiration level where individuals are easy to be satisfied with their current payoffs, different strategies can coexist. With the increase of aspiration level, unsatisfied individuals are likely to turn to compliers and build long-term reciprocity with their neighbors. However, at a high aspiration level, individuals are difficult to be satisfied with their payoffs and may randomly change their behaviors. Thus proper aspiration level promotes the emergence of generous behavior in the spatial prisoner’s dilemma game.

Suggested Citation

  • Zhi-Hai Rong & Qian Zhao & Zhi-Xi Wu & Tao Zhou & Chi Kong Tse, 2016. "Proper aspiration level promotes generous behavior in the spatial prisoner’s dilemma game," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(7), pages 1-7, July.
  • Handle: RePEc:spr:eurphb:v:89:y:2016:i:7:d:10.1140_epjb_e2016-70286-0
    DOI: 10.1140/epjb/e2016-70286-0
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    Citations

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    Cited by:

    1. Wang, Si-Yi & Liu, Yan-Ping & Zhang, Feng & Wang, Rui-Wu, 2021. "Super-rational aspiration induced strategy updating promotes cooperation in the asymmetric prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 403(C).
    2. Ding, Hong & Xu, Jia-Hao & Wang, Zhen & Ren, Yi-Zhi & Cui, Guang-Hai, 2018. "Subsidy strategy based on history information can stimulate voluntary vaccination behaviors on seasonal diseases," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 390-399.
    3. Wang, Zhen & Zhang, Geng-shun & Ding, Hong & Cui, Guang-Hai & Yao, Ye, 2019. "Strategy imitation behavior driven influence adjustment promotes cooperation in spatial prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    4. Chen, Wei & Wang, Jianwei & Yu, Fengyuan & He, Jialu & Xu, Wenshu & Dai, Wenhui, 2024. "Successful initial positioning of non-cooperative individuals in cooperative populations effectively hinders cooperation prosperity," Applied Mathematics and Computation, Elsevier, vol. 462(C).
    5. Wang, Junfang & Shen, Aizhong, 2024. "The synergy of elimination and zero-determinant strategy on dynamic games," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    6. Li, Cong & Xu, Hedong & Fan, Suohai, 2020. "Synergistic effects of self-optimization and imitation rules on the evolution of cooperation in the investor sharing game," Applied Mathematics and Computation, Elsevier, vol. 370(C).
    7. Han, Zhen & Zhu, Peican & Shi, Juan, 2023. "Novel payoff calculation resolves social dilemmas in networks," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    8. Ding, Hong & Zhang, Geng-shun & Wang, Shi-hao & Li, Juan & Wang, Zhen, 2019. "Q-learning boosts the evolution of cooperation in structured population by involving extortion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    9. Xia, Ke, 2021. "The characteristics of average abundance function of multi-player threshold public goods evolutionary game model under redistribution mechanism," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    10. Liu, Run-Ran & Jia, Chun-Xiao & Rong, Zhihai, 2019. "Effects of enhancement level on evolutionary public goods game with payoff aspirations," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 242-248.
    11. Liu, Yuanming & Huang, Changwei & Dai, Qionglin, 2018. "Preferential selection based on strategy persistence and memory promotes cooperation in evolutionary prisoner’s dilemma games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 481-489.
    12. Cui, Guang-Hai & Wang, Zhen & Yang, Yan-Cun & Tian, Sheng-Wen & Yue, Jun, 2018. "Heterogeneous game resource distributions promote cooperation in spatial prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1191-1200.
    13. Xia, Ke, 2021. "Average abundance function of multi-player threshold public goods without initial endowment evolutionary game model under differential aspiration levels and redistribution mechanism," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    14. Shen, Aizhong & Gao, Zili & Cui, Dan & Gu, Chen, 2024. "Extortion evolutionary game on scale-free networks with tunable clustering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).

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