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Migration As A Mechanism To Promote Cooperation

Author

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  • DIRK HELBING

    (ETH Zurich, UNO D11, Universitätstr. 41, CH-8092 Zurich, Switzerland)

  • WENJIAN YU

    (ETH Zurich, UNO D11, Universitätstr. 41, CH-8092 Zurich, Switzerland)

Abstract

A unified approach is proposed, which integrates game-theoretical models with models of directed motion. Specifically, strategic interactions in space and imitation of more successful neighboring strategies, as studied by spatial games, are combined with success-driven migration based on "test interactions" or wealth-related "neighborhood tagging." It turns out that such directed migration allows cooperators to evade defectors and (in constrast to purely diffusive motion) also to find other cooperators in order to form clusters ("islands of cooperation"). This can increase the cooperation to a great extent. Moreover, success-driven motion leads to interesting spatiotemporal pattern-formation phenomena, which are clearly different from those produced by previously studied spatial games. Despite the simplicity of the model, the forming patterns appear to realistically represent many stylized facts of social interactions, particularly phenomena such as social networking, urban aggregation, social segregation or turn-taking. Furthermore, migration games offer a game-theoretical explanation of social attraction and repulsion, based on payoff-related mobility, and they display a larger variety than conventional games, as their behavior is not invariant to shifting all payoffs by a constant amount. In summary, the combination of strategic interactions and imitation with models of directed motion has high potential for understanding empirical observations in the social, biological and economic sciences from a game-theoretical point of view. Finally, the breakdown of cooperation in the prisoner's dilemma at high values of temptation is explained by configurational analysis.

Suggested Citation

  • Dirk Helbing & Wenjian Yu, 2008. "Migration As A Mechanism To Promote Cooperation," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 11(04), pages 641-652.
  • Handle: RePEc:wsi:acsxxx:v:11:y:2008:i:04:n:s0219525908001866
    DOI: 10.1142/S0219525908001866
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    References listed on IDEAS

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    1. Thomas Lux & Eleni Samanidou & Stefan Reitz (ed.), 2005. "Nonlinear Dynamics and Heterogeneous Interacting Agents," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-540-27296-0, December.
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    Cited by:

    1. 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).
    2. Trenchard, Hugh, 2015. "The peloton superorganism and protocooperative behavior," Applied Mathematics and Computation, Elsevier, vol. 270(C), pages 179-192.
    3. Zhang, Jianlei & Zhang, Chunyan & Chu, Tianguang, 2011. "The evolution of cooperation in spatial groups," Chaos, Solitons & Fractals, Elsevier, vol. 44(1), pages 131-136.
    4. Charles G Nathanson & Corina E Tarnita & Martin A Nowak, 2009. "Calculating Evolutionary Dynamics in Structured Populations," PLOS Computational Biology, Public Library of Science, vol. 5(12), pages 1-7, December.
    5. Chiong, Raymond & Kirley, Michael, 2012. "Random mobility and the evolution of cooperation in spatial N-player iterated Prisoner’s Dilemma games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(15), pages 3915-3923.
    6. He, Zhixue & Geng, Yini & Shen, Chen & Shi, Lei, 2020. "Evolution of cooperation in the spatial prisoner’s dilemma game with extortion strategy under win-stay-lose-move rule," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).
    7. Li, Yan & Ye, Hang, 2015. "Effect of migration based on strategy and cost on the evolution of cooperation," Chaos, Solitons & Fractals, Elsevier, vol. 76(C), pages 156-165.
    8. Zhang, Chunyan & Zhang, Jianlei & Xie, Guangming, 2014. "Evolution of cooperation among game players with non-uniform migration scopes," Chaos, Solitons & Fractals, Elsevier, vol. 59(C), pages 103-111.
    9. Shilin Xiao & Liming Zhang & Haihong Li & Qionglin Dai & Junzhong Yang, 2022. "Environment-driven migration enhances cooperation in evolutionary public goods games," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 95(4), pages 1-9, April.
    10. Guo, Tian & He, Zhixue & Shi, Lei, 2023. "Self-organization in mobile populations promotes the evolution of altruistic punishment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    11. Genki Ichinose & Masaya Saito & Shinsuke Suzuki, 2013. "Collective Chasing Behavior between Cooperators and Defectors in the Spatial Prisoner’s Dilemma," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-10, July.
    12. Tao Wang & Keke Huang & Zhen Wang & Xiaoping Zheng, 2015. "Impact of Small Groups with Heterogeneous Preference on Behavioral Evolution in Population Evacuation," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-13, March.
    13. Lin, Hai & Yang, Dong-Ping & Shuai, J.W., 2011. "Cooperation among mobile individuals with payoff expectations in the spatial prisoner’s dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 44(1), pages 153-159.
    14. Zheng, Xiaoping & Cheng, Yuan, 2011. "Conflict game in evacuation process: A study combining Cellular Automata model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(6), pages 1042-1050.
    15. Ren, Yizhi & Chen, Xiangyu & Wang, Zhen & Shi, Benyun & Cui, Guanghai & Wu, Ting & Choo, Kim-Kwang Raymond, 2018. "Neighbor-considered migration facilitates cooperation in prisoner’s dilemma games," Applied Mathematics and Computation, Elsevier, vol. 323(C), pages 95-105.

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