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Coevolution of discrete, mixed, and continuous strategy systems boosts in the spatial prisoner's dilemma and chicken games

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  • Tanimoto, Jun

Abstract

A coevolutionary model by which both the strategy system and strategy value itself are allowed to adapt is established in the framework of spatial 2×2 games. Agents decide to update their behaviors in accordance with a discrete strategy (with a binary strategy set comprising only either cooperation (C) or defection (D)), mixed strategy, or continuous strategy. Because of the evolutionary advantage of the mixed strategy, which allows relatively high cooperators to offer defection to their defective neighbors to avoid exploitation by them, we found that the mixed strategy diffuses to the entire society in most of the dilemma region, and uses robust cooperation to increase the agents’ typical payoffs.

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  • Tanimoto, Jun, 2017. "Coevolution of discrete, mixed, and continuous strategy systems boosts in the spatial prisoner's dilemma and chicken games," Applied Mathematics and Computation, Elsevier, vol. 304(C), pages 20-27.
    • Handle: RePEc:eee:apmaco:v:304:y:2017:i:c:p:20-27
    DOI: 10.1016/j.amc.2017.01.015
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    References listed on IDEAS

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    1. Kokubo, Satoshi & Wang, Zhen & Tanimoto, Jun, 2015. "Spatial reciprocity for discrete, continuous and mixed strategy setups," Applied Mathematics and Computation, Elsevier, vol. 259(C), pages 552-568.
    2. Tanimoto, Jun, 2015. "The impact of initial cooperation fraction on the evolutionary fate in a spatial prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 263(C), pages 171-188.
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    Cited by:

    1. Liu, Chen & Guo, Hao & Li, Zhibin & Gao, Xiaoyuan & Li, Shudong, 2019. "Coevolution of multi-game resolves social dilemma in network population," Applied Mathematics and Computation, Elsevier, vol. 341(C), pages 402-407.
    2. Zheng, Liping & Xu, Hedong & Tian, Cunzhi & Fan, Suohai, 2021. "Evolutionary dynamics of information in the market: Transmission and trust," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    3. Mo, Fei & Han, Wenchen, 2024. "Long homogeneous payoff records with the latest strategy promotes the cooperation," Applied Mathematics and Computation, Elsevier, vol. 476(C).
    4. Lv, Shaojie & Wang, Xianjia, 2020. "The impact of heterogeneous investments on the evolution of cooperation in public goods game with exclusion," Applied Mathematics and Computation, Elsevier, vol. 372(C).
    5. Liu, Chengwei & Wang, Juan & Li, Xiaopeng & Xia, Chengyi, 2020. "The link weight adjustment considering historical strategy promotes the cooperation in the spatial prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
    6. Ye, Wenxing & Fan, Suohai, 2020. "Evolutionary traveler’s dilemma game based on particle swarm optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 544(C).
    7. Flores, Lucas S. & Amaral, Marco A. & Vainstein, Mendeli H. & Fernandes, Heitor C.M., 2022. "Cooperation in regular lattices," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).

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