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The effect of aspiration on the evolution of cooperation in spatial multigame

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  • Guo, Tian
  • Guo, Mi
  • Zhang, Yan
  • Liang, Shuanglu

Abstract

In this paper, we explore the effect of aspiration on the evolution of cooperation in the spatial multigame. In detail, the whole populations were classified into two types. For players of type A, they play prisoner’s dilemma game, and for players of type B, they play snowdrift game. Once someone who are unsatisfied his performance, he is going to another type, otherwise, he will keep his current type constant. Through numerical simulation, we find that cooperation can be enhanced and even dominate the whole networks for moderate aspiration level. Besides, when the aspiration level is too large, cooperation level would be restrained. For these observations, we give an explanation from the points of evolutionary snapshots.

Suggested Citation

  • Guo, Tian & Guo, Mi & Zhang, Yan & Liang, Shuanglu, 2019. "The effect of aspiration on the evolution of cooperation in spatial multigame," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 27-32.
    • Handle: RePEc:eee:phsmap:v:525:y:2019:i:c:p:27-32
    DOI: 10.1016/j.physa.2019.03.031
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    References listed on IDEAS

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    Cited by:

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    3. Liu, Yujie & Li, Zemin & Jin, Xing & Tao, Yuchen & Ding, Hong & Wang, Zhen, 2022. "The effect of perceptions competition and learning costs on cooperation in spatial evolutionary multigames," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    4. Wu, Yu’e & Zhang, Zhipeng & Yang, Guoli & Liu, Haixin & Zhang, Qingfeng, 2022. "Evolution of cooperation driven by diversity on a double-layer square lattice," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    5. 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).
    6. Wu, Yu’e & Zhang, Zhipeng & Wang, Xinyu & Yan, Ming & Zhang, Qingfeng & Zhang, Shuhua, 2021. "Evolution of cooperation in the multigame on a two-layer square network," Applied Mathematics and Computation, Elsevier, vol. 400(C).
    7. Deng, Xinyang & Jiang, Wen & Wang, Zhen, 2020. "An Information Source Selection Model Based on Evolutionary Game Theory," Applied Mathematics and Computation, Elsevier, vol. 385(C).
    8. Han, Xu & Zhao, Xiaowei & Xia, Haoxiang, 2021. "Evolution of cooperation through aspiration-based adjustment of interaction range in spatial prisoner’s dilemma game," Applied Mathematics and Computation, Elsevier, vol. 393(C).
    9. Geng, Yini & Liu, Yifan & Lu, Yikang & Shen, Chen & Shi, Lei, 2022. "Reinforcement learning explains various conditional cooperation," Applied Mathematics and Computation, Elsevier, vol. 427(C).
    10. Guan, Kaixuan & Chen, Yuyou & Zheng, Wanjun & Zeng, Lulu & Ye, Hang, 2022. "Costly signals can facilitate cooperation and punishment in the prisoner’s dilemma," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    11. Gheorge-Florentin Miulescu & Paul Marinescu & Sorin-George Toma, 2019. "Competitive Cooperation – Market Development Instrument," Manager Journal, Faculty of Business and Administration, University of Bucharest, vol. 29(1), pages 106-113, December.
    12. Chu, Chen & Cui, Simin & Yuan, Zheng & Yu, Chunbin, 2022. "A win-stay-lose-learn mechanism based on aspiration can promote cooperation in a multigame," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
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    14. Bin, Liu & Yue, Wu, 2023. "Co-evolution of reputation-based preference selection and resource allocation with multigame on interdependent networks," Applied Mathematics and Computation, Elsevier, vol. 456(C).

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