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A co-evolutionary model combined mixed-strategy and network adaptation by severing disassortative neighbors promotes cooperation in prisoner’s dilemma games

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  • Miyaji, Kohei
  • Tanimoto, Jun

Abstract

A co-evolutionary model of both network and mixed strategy is proposed in this study. The assigned strategy si of agent i is defined by a real number ranging from 0 to 1, which probabilistically ordains a subsequent action of either cooperation or defection as the agent’s offer. We assume a network dynamic to support or hamper the enhancement of cooperation, where an agent severs a link with the neighbor who has the most disassortative strategy. This means that an agent tends to maintain interactions only with neighbors that resemble the agent. A series of numerical simulations reveal that our “assortative grouping” framework enhances cooperation. Interestingly, when a low network adaptation speed and a certain degree of strategy copy error are presumed, phenomenal network heterogeneity evolves, one that realizes more significant cooperation as compared to error-free cases.

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  • Miyaji, Kohei & Tanimoto, Jun, 2021. "A co-evolutionary model combined mixed-strategy and network adaptation by severing disassortative neighbors promotes cooperation in prisoner’s dilemma games," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    • Handle: RePEc:eee:chsofr:v:143:y:2021:i:c:s0960077920309942
    DOI: 10.1016/j.chaos.2020.110603
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    References listed on IDEAS

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    1. Jorgen W. Weibull, 1997. "Evolutionary Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262731215, April.
    2. repec:hhs:iuiwop:487 is not listed on IDEAS
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    Cited by:

    1. Guo, Yujie & Zhang, Liming & Li, Haihong & Dai, Qionglin & Yang, Junzhong, 2023. "Network adaption based on environment feedback promotes cooperation in co-evolutionary games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 617(C).
    2. Khan, Md. Mamun-Ur-Rashid & Arefin, Md. Rajib & Tanimoto, Jun, 2022. "Investigating the trade-off between self-quarantine and forced quarantine provisions to control an epidemic: An evolutionary approach," Applied Mathematics and Computation, Elsevier, vol. 432(C).
    3. Gao, Liyan & Pan, Qiuhui & He, Mingfeng, 2022. "Advanced defensive cooperators promote cooperation in the prisoner’s dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    4. Liu, Dandan & Wang, Delu & Mao, Jinqi, 2023. "Study on policy synergy strategy of the central government and local governments in the process of coal de-capacity: Based on a two-stage evolutionary game method," Resources Policy, Elsevier, vol. 80(C).
    5. Bi, Yan & Yang, Hui, 2023. "Based on reputation consistent strategy times promotes cooperation in spatial prisoner’s dilemma game," Applied Mathematics and Computation, Elsevier, vol. 444(C).

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