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Migration based on environment comparison promotes cooperation in evolutionary games

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  • Zhang, Liming
  • Li, Haihong
  • Dai, Qionglin
  • Yang, Junzhong

Abstract

Human beings and natural creatures often migrate in search of better environments. When both local and global environments can be perceived by individuals, they may determine whether to migrate or not based on the comparison. If the individuals realize the local environments are worse than the global ones, they are more likely to leave their original place. Otherwise, they may choose to stay still. Considering these, we study the evolutionary games in a dynamically changing population on a square lattice, in which the players migrate based on the comparison between local and global environments. The simulation results show that cooperation can be significantly promoted. By examining the strategy patterns during the evolution, we find there exist two evolutionary stages that account for the enhancement of cooperation. One is the clustering of cooperators, in which cooperator clusters get strengthened by slow migration of cooperators and fast migration of defectors. The other is the coalescence of cooperator clusters, which induces further increment of the cooperation level. Besides, we investigate the effects of two different types of noises on cooperation, which are introduced in migration and in strategy imitation, respectively. The results reveal that cooperation could be enhanced by low migration noise whereas high strategy-adoption noise.

Suggested Citation

  • Zhang, Liming & Li, Haihong & Dai, Qionglin & Yang, Junzhong, 2022. "Migration based on environment comparison promotes cooperation in evolutionary games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 595(C).
    • Handle: RePEc:eee:phsmap:v:595:y:2022:i:c:s0378437122001224
    DOI: 10.1016/j.physa.2022.127073
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    References listed on IDEAS

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    Cited by:

    1. Lee, Hsuan-Wei & Cleveland, Colin & Szolnoki, Attila, 2023. "Group-size dependent synergy in heterogeneous populations," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    2. Zhao, Xiaowei & Xia, Haoxiang, 2023. "Information accuracy of migration and imitation influences the evolution of cooperation in spatial prisoner's dilemma," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    3. Yang, Yixin & Pan, Qiuhui & He, Mingfeng, 2023. "The influence of environment-based autonomous mobility on the evolution of cooperation," Chaos, Solitons & Fractals, Elsevier, vol. 169(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. 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).

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