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Coevolution of multi-game resolves social dilemma in network population

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  • Liu, Chen
  • Guo, Hao
  • Li, Zhibin
  • Gao, Xiaoyuan
  • Li, Shudong

Abstract

It is an open question to understand the emergence and maintenance of cooperation in nature and society. Aim to this issue, evolutionary game theory in networked population and its various derivations, like mixing game and multi-game, have proved an effective way to resolve the social dilemma. In this work, we propose the coevolution framework of strategy and multi-game: if a player, in prisoner's dilemma game, successively keeps its strategy constant for several times (referred as memory step), it will have opportunity to participate in snow drift game, which has lower dilemma strength than prisoner's dilemma game. Of particular, it is unveiled that for short memory step, the larger the value of sucker's payoff is, the higher frequency of cooperation will be. While for long memory step, middle sucker's payoff provides a best environment for cooperation. For all these findings, we also provide theoretical analysis, which guarantees further validation.

Suggested Citation

  • Liu, Chen & Guo, Hao & Li, Zhibin & Gao, Xiaoyuan & Li, Shudong, 2019. "Coevolution of multi-game resolves social dilemma in network population," Applied Mathematics and Computation, Elsevier, vol. 341(C), pages 402-407.
  • Handle: RePEc:eee:apmaco:v:341:y:2019:i:c:p:402-407
    DOI: 10.1016/j.amc.2018.09.019
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    16. Peican Zhu & Xin Hou & Yangming Guo & Jiwei Xu & Jinzhuo Liu, 2021. "Investigating the effects of updating rules on cooperation by incorporating interactive diversity," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(2), pages 1-8, February.
    17. Gholamreza Askari & Madjid Eshaghi Gordji & Somayeh Shabani & Jose Antonio Filipe, 2020. "Game Theory and Trade Tensions between Advanced Economies," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 50-65.
    18. Chu, Chen & Zhai, Yao & Mu, Chunjiang & Hu, Die & Li, Tong & Shi, Lei, 2019. "Reputation-based popularity promotes cooperation in the spatial prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 362(C), pages 1-1.
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    21. Li, Shudong & Jiang, Laiyuan & Wu, Xiaobo & Han, Weihong & Zhao, Dawei & Wang, Zhen, 2021. "A weighted network community detection algorithm based on deep learning," Applied Mathematics and Computation, Elsevier, vol. 401(C).

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