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The effects of aspiration under multiple strategy updating rules on cooperation in prisoner's dilemma game

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  • You, Tao
  • Shi, Liang
  • Wang, Xiaoyu
  • Mengibaev, Muslimbek
  • Zhang, Ying
  • Zhang, Peng

Abstract

In the traditional game theory, a widely accepted assumption is that the participants are completely rational and under the condition of complete information. But in the realistic economy experiences, the participants’ conditions of complete rationality and information are usually hard to be fulfilled. The mutations, un-fixed mechanisms, and policy variations usually challenge the process of natural game evolution. In this work, we mainly study how to make the iterative transformation of policy updating rules to maximize their own benefits in the case of heterogeneous updating rules. In particular, a novel mutation mechanism is developed to study the cooperation situation in natural selection by introducing two different proportion groups in the population, one is based on imitation, the other is based on aspiration level, and both proportions can transform each other under certain conditions at the end of each generation. The mutation of the individual mechanism may occur, it is found that the population proportion and individual rule mutation rate have a strong stabilizing effect on population cooperation under this mixed mechanism, and the lower aspiration level has a certain promoting effect on cooperation as well.

Suggested Citation

  • You, Tao & Shi, Liang & Wang, Xiaoyu & Mengibaev, Muslimbek & Zhang, Ying & Zhang, Peng, 2021. "The effects of aspiration under multiple strategy updating rules on cooperation in prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 394(C).
    • Handle: RePEc:eee:apmaco:v:394:y:2021:i:c:s0096300320307232
    DOI: 10.1016/j.amc.2020.125770
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    References listed on IDEAS

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    Cited by:

    1. Chen, Qin & Pan, Qiuhui & He, Mingfeng, 2022. "The influence of quasi-cooperative strategy on social dilemma evolution," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    2. He, Jialu & Wang, Jianwei & Yu, Fengyuan & Chen, Wei & Li, Bofan, 2022. "The slow but persistent self-improvement boosts group cooperation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    3. Zhang, Mingzhen & Yang, Naiding & Zhu, Xianglin & Wang, Yan, 2022. "The evolution of cooperation in public goods games on the scale-free community network under multiple strategy-updating rules," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    4. Wang, Chaoqian & Huang, Chaochao & Pan, Qiuhui & He, Mingfeng, 2022. "Modeling the social dilemma of involution on a square lattice," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    5. 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).
    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).

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