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Diversity of neighborhoods promotes cooperation in evolutionary social dilemmas

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  • Ma, Yongjuan
  • Lu, Jun
  • Shi, Lei

Abstract

Explaining the evolution of cooperative behavior is one of the most important and interesting problems in a myriad of disciplines, such as evolutionary biology, mathematics, statistical physics, social science and economics Up to now, there have been a great number of works aiming to this issue with the help of evolutionary game theory. However, vast majority of existing literatures simply assume that the interaction neighborhood and replacement neighborhood are symmetric, which seems inconsistent with real-world cases. In this paper, we consider the asymmetrical neighborhood: player of type A, whose factor is controlled by a parameter τ, has four interaction neighbors and four replacement neighbors, while player of type B, whose factor is controlled by a parameter 1−τ, possess eight interaction neighbors and four replacement neighbors. By means of numerous Monte Carlo simulations, we found that middle τ can make the cooperation reach the highest level While for this finding, its robustness can be further validated in more games.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:phsmap:v:468:y:2017:i:c:p:212-218
    DOI: 10.1016/j.physa.2016.11.010
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    Citations

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    Cited by:

    1. Wu, Yu’e & Zhang, Zhipeng & Chang, Shuhua, 2017. "Effect of self-interaction on the evolution of cooperation in complex topologies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 191-197.
    2. Chen, Qin & Pan, Qiuhui & He, Mingfeng, 2022. "The influence of quasi-cooperative strategy on social dilemma evolution," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    3. 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).
    4. Yu, Fengyuan & Wang, Jianwei & He, Jialu, 2022. "Inequal dependence on members stabilizes cooperation in spatial public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    5. Liu, Yandi & Wang, Hexin & Ding, Yi & Yang, Xuan & Dai, Yu, 2022. "Can weak diversity help in propagating cooperation? Invasion of cooperators at the conformity-conflict boundary," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    6. Li, Xiaopeng & Wang, Zhonglin & Xu, Yan & Zhang, Hui & Yu, Guihai, 2024. "Asymmetrical interactions driven by strategic persistence effectively alleviate social dilemmas," Chaos, Solitons & Fractals, Elsevier, vol. 184(C).
    7. Liu, Yaojun & Liu, Xingwen, 2024. "Promotion of cooperation in evolutionary snowdrift game with heterogeneous memories," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).
    8. Liu, Yandi & Zheng, Tainian & Li, Yonghui & Dai, Yu, 2020. "Does the conformity save us when information advantage fails?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    9. 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).
    10. Han, Xu & Zhao, Xiaowei & Xia, Haoxiang, 2018. "Promotion of cooperation by adaptive interaction: The role of heterogeneity in neighborhoods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 483-491.
    11. 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.
    12. Pi, Jinxiu & Yang, Guanghui & Yang, Hui, 2022. "Evolutionary dynamics of cooperation in N-person snowdrift games with peer punishment and individual disguise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    13. Chen, Yu-Rong & Zhang, Xian-Xia & Yu, Yin-Sheng & Ma, Shi-Wei & Yang, Banghua, 2022. "Enhancing convergence efficiency of self-propelled agents using direction preference," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    14. Hadzibeganovic, Tarik & Stauffer, Dietrich & Han, Xiao-Pu, 2018. "Interplay between cooperation-enhancing mechanisms in evolutionary games with tag-mediated interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 676-690.

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