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Environment-driven migration enhances cooperation in evolutionary public goods games

  • Regular Article - Statistical and Nonlinear Physics
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Abstract

Migration plays a critical role in the evolution of cooperation under the framework of evolutionary game theory. Previous studies have demonstrated that individuals might make their migration decisions based on various information, for example, their current cooperative environments, potential advantages of new places, and their own aspirations. In reality, people may perceive environment information and make decisions based on these information. In this paper, we introduce an environment-driven migration into evolutionary public goods games which are carried out on a two-dimensional plane, where individuals decide whether to migrate according to the probabilities determined by the differences between the local and global cooperative environments. We find that such an environment-driven migration can effectively enhance cooperation. Furthermore, there exists an optimal migration noise that leads to a highest cooperation level. In addition, we also find that appropriate moving speeds and migration tendencies, as well as relatively low population densities in the model are more favorable to the evolution of cooperation.

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Data Availability Statement

This manuscript has no associated data or the data will not be deposited. [Authors’ comment: The results are obtained mainly through numerical simulation, and all the related data have been shown in the figures of the article.]

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Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grant no. 11805021 and the BUPT Excellent Ph.D. Students Foundation under Grant no. CX2021226.

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Authors and Affiliations

  1. School of Science, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Shilin Xiao, Liming Zhang, Haihong Li, Qionglin Dai & Junzhong Yang

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  1. Shilin Xiao
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  2. Liming Zhang
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  3. Haihong Li
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  4. Qionglin Dai
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  5. Junzhong Yang
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Contributions

SX and LZ: conceptualization, methodology, investigation, writing-original draft. HL: conceptualization, methodology, visualization, Software. QD: writing-original draft, formal analysis, funding acquisition, validation. JY: validation, supervision.

Corresponding authors

Correspondence to Liming Zhang or Qionglin Dai.

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Xiao, S., Zhang, L., Li, H. et al. Environment-driven migration enhances cooperation in evolutionary public goods games. Eur. Phys. J. B 95, 67 (2022). https://doi.org/10.1140/epjb/s10051-022-00327-8

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