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Asymmetric evaluation promotes cooperation in network population

Author

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  • Shen, Chen
  • Li, Xiaoping
  • Shi, Lei
  • Deng, Zhenghong

Abstract

The evolution of cooperation remains a fundamental challenge in human society. Many previous studies investigated these questions via spatial reciprocity, where players obtain their payoffs by interacting with their direct neighbors. It has also been verified that environmental factors can influence the evolution of cooperation theoretically and empirically. In reality, however, individuals may have the limit knowledge about their indirect neighbors. Inspired by this fact, we consider an asymmetric fitness calculation mechanism, which only integrates the environment factors into the focal player, to explore the evolution of cooperation. Here, the environmental factor is defined as the average payoff of all individual neighbors, which is regulated by a tunable parameter u. Through numerical simulation, we find that, compared with the traditional version (u=0), that the cooperation level can be greatly enhanced when u is positive. Interestingly, the larger the value of u, the higher the level of cooperation. Finally, to explore the generality of this finding, we have tested the results on different topologies.

Suggested Citation

  • Shen, Chen & Li, Xiaoping & Shi, Lei & Deng, Zhenghong, 2017. "Asymmetric evaluation promotes cooperation in network population," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 391-397.
    • Handle: RePEc:eee:phsmap:v:474:y:2017:i:c:p:391-397
    DOI: 10.1016/j.physa.2017.02.005
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    References listed on IDEAS

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    Cited by:

    1. Deng, Zhilong & Deming, Mao & Dameng, Dai, 2018. "Asymmetric learning ability promotes cooperation in structured populations," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 88-91.
    2. Chang, Shuhua & Zhang, Zhipeng & Wu, Yu’e & Xie, Yunya, 2018. "Cooperation is enhanced by inhomogeneous inertia in spatial prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 419-425.
    3. Liu, Jinzhuo & Li, Tong & Wang, Wei & Zhao, Na & Hang, Feilu, 2018. "Impact of strategy-neutral rewarding on the evolution of cooperative behavior," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 76-79.
    4. Xie, Yunya & Zhang, Shuhua & Zhang, Zhipeng & Bu, Hongyu, 2020. "Impact of binary social status with hierarchical punishment on the evolution of cooperation in the spatial prisoner’s dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 130(C).
    5. Zhang, Xin-Jie & Tang, Yong & Xiong, Jason & Wang, Wei-Jia & Zhang, Yi-Cheng, 2020. "Ranking game on networks: The evolution of hierarchical society," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    6. Liu, Jinzhuo & Meng, Haoran & Wang, Wei & Li, Tong & Yu, Yong, 2018. "Synergy punishment promotes cooperation in spatial public good game," Chaos, Solitons & Fractals, Elsevier, vol. 109(C), pages 214-218.
    7. Liu, Xuesong & Pan, Qiuhui & He, Mingfeng & Liu, Aizhi, 2019. "Promotion of cooperation in evolutionary game dynamics under asymmetric information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 258-266.
    8. Liu, Jinzhuo & Meng, Haoran & Wang, Wei & Xie, Zhongwen & Yu, Qian, 2019. "Evolution of cooperation on independent networks: The influence of asymmetric information sharing updating mechanism," Applied Mathematics and Computation, Elsevier, vol. 340(C), pages 234-241.
    9. Jinzhuo Liu & Mao Peng & Yunchen Peng & Yong Li & Chen Chu & Xiaoyu Li & Qing Liu, 2021. "Effects of inequality on a spatial evolutionary public goods game," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(8), pages 1-7, August.

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