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A win-switch-lose-stay strategy promotes cooperation in the evolutionary games

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  • Shu, Feng

Abstract

The subject of how and why cooperation emerges in real world has been intensively investigated. A number of mechanisms have been found to favor cooperation in ecological systems and human societies. Here, we propose a win-switch-lose-stay strategy whose core lies in two aspects: (i) An individual, according to Fermi updating rule, first selects one neighbor stochastically from all its nearest neighbors to play the game to update its strategy of the first round, and memories the selected neighbor. (ii) The individual interacts with the selected neighbor in the last round if its accumulated payoff is lower than that of the selected neighbor, otherwise the selected neighbor randomly switches to another of its rest neighbors. Other individuals also follow the updating rule and repeat this evolutionary process. Simulation results reveal that the proposed strategy can remarkably promote cooperation in several social dilemmas, including the prisoner’s dilemma, the snowdrift game and the stag-hunt game.

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  • Shu, Feng, 2020. "A win-switch-lose-stay strategy promotes cooperation in the evolutionary games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
    • Handle: RePEc:eee:phsmap:v:555:y:2020:i:c:s0378437120302934
    DOI: 10.1016/j.physa.2020.124605
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    References listed on IDEAS

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    1. Shu, Feng & Li, Min & Liu, Xingwen, 2019. "Memory mechanism with weighting promotes cooperation in the evolutionary games," Chaos, Solitons & Fractals, Elsevier, vol. 120(C), pages 17-24.
    2. Chen Chu & Jinzhuo Liu & Chen Shen & Jiahua Jin & Lei Shi, 2017. "Win-stay-lose-learn promotes cooperation in the prisoner’s dilemma game with voluntary participation," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-8, February.
    3. Chen Shen & Chen Chu & Yini Geng & Jiahua Jin & Fei Chen & Lei Shi, 2018. "Cooperation enhanced by the coevolution of teaching activity in evolutionary prisoner's dilemma games with voluntary participation," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-8, February.
    4. He, Nanrong & Chen, Xiaojie & Szolnoki, Attila, 2019. "Central governance based on monitoring and reporting solves the collective-risk social dilemma," Applied Mathematics and Computation, Elsevier, vol. 347(C), pages 334-341.
    5. Ma, Yongjuan & Lu, Jun & Shi, Lei, 2017. "Diversity of neighborhoods promotes cooperation in evolutionary social dilemmas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 212-218.
    6. Marco Alberto Javarone, 2016. "Statistical physics of the spatial Prisoner’s Dilemma with memory-aware agents," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(2), pages 1-6, February.
    7. Yongkui Liu & Xiaojie Chen & Lin Zhang & Long Wang & Matjaž Perc, 2012. "Win-Stay-Lose-Learn Promotes Cooperation in the Spatial Prisoner's Dilemma Game," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-8, February.
    8. Iwata, Manabu & Akiyama, Eizo, 2016. "Heterogeneity of link weight and the evolution of cooperation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 224-234.
    9. 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.
    10. Su, Qi & Li, Aming & Wang, Long, 2017. "Spatial structure favors cooperative behavior in the snowdrift game with multiple interactive dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 299-306.
    11. Hu, Kaipeng & Guo, Hao & Geng, Yini & Shi, Lei, 2019. "The effect of conformity on the evolution of cooperation in multigame," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 267-272.
    12. Ren, Yizhi & Chen, Xiangyu & Wang, Zhen & Shi, Benyun & Cui, Guanghai & Wu, Ting & Choo, Kim-Kwang Raymond, 2018. "Neighbor-considered migration facilitates cooperation in prisoner’s dilemma games," Applied Mathematics and Computation, Elsevier, vol. 323(C), pages 95-105.
    13. Deng, Xinyang & Zhang, Zhipeng & Deng, Yong & Liu, Qi & Chang, Shuhua, 2016. "Self-adaptive win-stay-lose-shift reference selection mechanism promotes cooperation on a square lattice," Applied Mathematics and Computation, Elsevier, vol. 284(C), pages 322-331.
    14. Christoph Hauert & Michael Doebeli, 2004. "Spatial structure often inhibits the evolution of cooperation in the snowdrift game," Nature, Nature, vol. 428(6983), pages 643-646, April.
    15. Marco Alberto Javarone, 2016. "Statistical physics of the spatial Prisoner’s Dilemma with memory-aware agents," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(2), pages 1-6, February.
    16. Wang, Qiang & He, Nanrong & Chen, Xiaojie, 2018. "Replicator dynamics for public goods game with resource allocation in large populations," Applied Mathematics and Computation, Elsevier, vol. 328(C), pages 162-170.
    17. Ming-Jian Fu & Han-Xin Yang, 2018. "Stochastic win-stay-lose-learn promotes cooperation in the spatial public goods game," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 29(04), pages 1-8, April.
    18. Zhang, W. & Li, Y.S. & Xu, C. & Hui, P.M., 2016. "Cooperative behavior and phase transitions in co-evolving stag hunt game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 161-169.
    19. Xiaojie Chen & Attila Szolnoki, 2018. "Punishment and inspection for governing the commons in a feedback-evolving game," PLOS Computational Biology, Public Library of Science, vol. 14(7), pages 1-15, July.
    20. Shu, Feng & Liu, Yaojun & Liu, Xingwen & Zhou, Xiaobing, 2019. "Memory-based conformity enhances cooperation in social dilemmas," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 480-490.
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    Cited by:

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