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Coevolving agent strategies and network topology for the public goods games

Author

Listed:
  • C. Y. Zhang
  • J. L. Zhang
  • G. M. Xie
  • L. Wang

Abstract

Much of human cooperation remains an evolutionary riddle. Coevolutionary public goods games in structured populations are studied where players can change from an unproductive public goods game to a productive one, by evaluating the productivity of the public goods games. In our model, each individual participates in games organized by its neighborhood plus by itself. Coevolution here refers to an evolutionary process entailing both deletion of existing links and addition of new links between agents that accompanies the evolution of their strategies. Furthermore, we investigate the effects of time scale separation of strategy and structure on cooperation level. This study presents the following: Foremost, we observe that high cooperation levels in public goods interactions are attained by the entangled coevolution of strategy and structure. Presented results also confirm that the resulting networks show many features of real systems, such as cooperative behavior and hierarchical clustering. The heterogeneity of the interaction network is held responsible for the observed promotion of cooperation. We hope our work may offer an explanation for the origin of large-scale cooperative behavior among unrelated individuals. Copyright EDP Sciences, SIF, Springer-Verlag Berlin Heidelberg 2011

Suggested Citation

  • C. Y. Zhang & J. L. Zhang & G. M. Xie & L. Wang, 2011. "Coevolving agent strategies and network topology for the public goods games," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 80(2), pages 217-222, March.
    • Handle: RePEc:spr:eurphb:v:80:y:2011:i:2:p:217-222
    DOI: 10.1140/epjb/e2011-10470-2
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    Citations

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    Cited by:

    1. Mark Broom & Igor V. Erovenko & Jan Rychtář, 2021. "Modelling Evolution in Structured Populations Involving Multiplayer Interactions," Dynamic Games and Applications, Springer, vol. 11(2), pages 270-293, June.
    2. Li, Zhi & Deng, Chuang & Suh, Il Hong, 2015. "Network topology control strategy based on spatial evolutionary public goods game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 16-23.
    3. Zhao, Jinqiu & Luo, Chao, 2019. "The effect of preferential teaching and memory on cooperation clusters in interdependent networks," Applied Mathematics and Computation, Elsevier, vol. 363(C), pages 1-1.
    4. 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).
    5. Han, Dun & Yan, Shuting & Li, Dandan, 2019. "The evolutionary public goods game model with punishment mechanism in an activity-driven network," Chaos, Solitons & Fractals, Elsevier, vol. 123(C), pages 254-259.
    6. Takesue, Hirofumi, 2021. "Symmetry breaking in the prisoner’s dilemma on two-layer dynamic multiplex networks," Applied Mathematics and Computation, Elsevier, vol. 388(C).
    7. Cardinot, Marcos & Griffith, Josephine & O’Riordan, Colm, 2018. "A further analysis of the role of heterogeneity in coevolutionary spatial games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 116-124.
    8. Hirofumi Takesue, 2020. "From defection to ingroup favoritism to cooperation: simulation analysis of the social dilemma in dynamic networks," Journal of Computational Social Science, Springer, vol. 3(1), pages 189-207, April.

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