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Popularity-driven strategy updating rule promotes cooperation in the spatial prisoner's dilemma game

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  • Xu, Jiwei
  • Deng, Zhenghong
  • Gao, Bo
  • Song, Qun
  • Tian, Zhihong
  • Wang, Qiuling
  • Gao, Mingyu
  • Niu, Zhenxi

Abstract

To explain the emergence and maintenance of cooperation is still a great challenge, many mechanisms have been put forward to solve it. Individual's popularity, which studied by many scholars, means the number of the same strategy adopted by its total neighbors. A well-known fact that high popularity often leads advantage position in the fierce competition and these individuals more likely to be imitated by others. In this paper, we consider a coevolutionary model to investigate the influence of popularity score on the evolution of cooperation, where individual with high popularity has larger ability to reproduce its strategy, whereas, individuals with low popularity have limited ability to reproduce their strategies. Numerical simulation results show that moderate range of popularity can promote cooperation, and the larger the value of Δ, the more sensitive of the reproductive ability, which leads to the higher level of cooperation. We further explain these phenomenon from the perspective of strategy conversion, it reveals that moderate popularity range enhances the reproductive ability and the cooperators can spread their strategies. Our findings may be useful for understanding the enduring cooperative behavior in the process of strategy reproduction.

Suggested Citation

  • Xu, Jiwei & Deng, Zhenghong & Gao, Bo & Song, Qun & Tian, Zhihong & Wang, Qiuling & Gao, Mingyu & Niu, Zhenxi, 2019. "Popularity-driven strategy updating rule promotes cooperation in the spatial prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 353(C), pages 82-87.
    • Handle: RePEc:eee:apmaco:v:353:y:2019:i:c:p:82-87
    DOI: 10.1016/j.amc.2019.01.060
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    Cited by:

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    2. Han, Ying & Song, Zhao & Sun, Jialong & Ma, Jiezhong & Guo, Yangming & Zhu, Peican, 2020. "Investing the effect of age and cooperation in spatial multigame," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    3. Xu, Jiwei & Deng, Zhenghong & Song, Qun & Chi, Qian & Wu, Tao & Huang, Yijie & Liu, Dan & Gao, Mingyu, 2020. "Multi-UAV counter-game model based on uncertain information," Applied Mathematics and Computation, Elsevier, vol. 366(C).
    4. Liao, Hui-Min & Hao, Qing-Yi & Qian, Jia-Li & Wu, Chao-Yun & Guo, Ning & Ling, Xiang, 2023. "Cooperative evolution under the joint influence of local popularity and global popularity," Applied Mathematics and Computation, Elsevier, vol. 439(C).
    5. Yunsheng Deng & Jihui Zhang, 2022. "The choice-decision based on memory and payoff favors cooperation in stag hunt game on interdependent networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 95(2), pages 1-13, February.
    6. Lu, Shounan & Dai, Jianhua & Zhu, Ge & Guo, Li, 2023. "Investigating the effectiveness of interaction-efficiency-driven strategy updating under progressive-interaction for the evolution of the prisoner's dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    7. Wang, Zi-Ren & Deng, Zheng-Hong & Wang, Huan-Bo & Li, HuXiong & X, Fei-Wang, 2022. "Uneven Resources network promotes cooperation in the prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 413(C).
    8. Pan, Qiuhui & Wang, Yue & He, Mingfeng, 2022. "Impacts of special cooperation strategy with reward and punishment mechanism on cooperation evolution," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).

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