IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v617y2023ics0378437123002443.html
   My bibliography  Save this article

Network adaption based on environment feedback promotes cooperation in co-evolutionary games

Author

Listed:
  • Guo, Yujie
  • Zhang, Liming
  • Li, Haihong
  • Dai, Qionglin
  • Yang, Junzhong

Abstract

In evolutionary games, the choices of individuals form the cooperation environments, and the environments in turn affect the behaviors of individuals. Such environment feedback can be utilized to facilitate the evolution of cooperation. On the other hand, adaptive social structures have been thought to promote cooperation, in which the individuals can switch their interacting neighbors. Here, we propose a co-evolutionary game model, in which individuals can adjust connections based on environment feedback during the evolution. In particular, the individuals determine whether to adjust their connections by comparing the local cooperation environment with the global one. Meanwhile, we use the parameter ω to adjust the time scale between the strategy evolution and the network adaptation in the co-evolutionary dynamics. Our results show that, the network adaption based on the environment feedback can significantly promote cooperation. We find that, relatively fast network adaptation (large ω) can better facilitate the evolution of cooperation. We further investigate how the rationality of individuals in network adaptation process affects the cooperation, and find that a high level of rationality is beneficial to improve cooperation. Through monitoring the local cooperation environments of the individuals, the fractions of the reconnecting individuals and the average degrees of cooperators and defectors, respectively, we provide some intuitive explanations for the promotion of cooperation by the co-evolutionary scheme. Our results may provide some references on the study about how to improve cooperation by adapting the social structures based on environment feedback in the real world.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:phsmap:v:617:y:2023:i:c:s0378437123002443
    DOI: 10.1016/j.physa.2023.128689
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437123002443
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2023.128689?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Takahiro Ezaki & Yutaka Horita & Masanori Takezawa & Naoki Masuda, 2016. "Reinforcement Learning Explains Conditional Cooperation and Its Moody Cousin," PLOS Computational Biology, Public Library of Science, vol. 12(7), pages 1-13, July.
    2. Du, Wen-Bo & Cao, Xian-Bin & Zhao, Lin & Hu, Mao-Bin, 2009. "Evolutionary games on scale-free networks with a preferential selection mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(20), pages 4509-4514.
    3. Song, Zhao & Guo, Hao & Jia, Danyang & Perc, Matjaž & Li, Xuelong & Wang, Zhen, 2021. "Third party interventions mitigate conflicts on interdependent networks," Applied Mathematics and Computation, Elsevier, vol. 403(C).
    4. Rui Cong & Bin Wu & Yuanying Qiu & Long Wang, 2012. "Evolution of Cooperation Driven by Reputation-Based Migration," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-7, May.
    5. Hisashi Ohtsuki & Christoph Hauert & Erez Lieberman & Martin A. Nowak, 2006. "A simple rule for the evolution of cooperation on graphs and social networks," Nature, Nature, vol. 441(7092), pages 502-505, May.
    6. Francisco C Santos & Jorge M Pacheco & Tom Lenaerts, 2006. "Cooperation Prevails When Individuals Adjust Their Social Ties," PLOS Computational Biology, Public Library of Science, vol. 2(10), pages 1-8, October.
    7. F. Fu & L.-H. Liu & L. Wang, 2007. "Evolutionary Prisoner's Dilemma on heterogeneous Newman-Watts small-world network," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 56(4), pages 367-372, April.
    8. David G. Rand & Martin A. Nowak, 2011. "The evolution of antisocial punishment in optional public goods games," Nature Communications, Nature, vol. 2(1), pages 1-7, September.
    9. Bin Wu & Da Zhou & Feng Fu & Qingjun Luo & Long Wang & Arne Traulsen, 2010. "Evolution of Cooperation on Stochastic Dynamical Networks," PLOS ONE, Public Library of Science, vol. 5(6), pages 1-7, June.
    10. 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.
    11. 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).
    12. A. Szolnoki & M. Perc, 2009. "Promoting cooperation in social dilemmas via simple coevolutionary rules," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 67(3), pages 337-344, February.
    13. Miyaji, Kohei & Tanimoto, Jun, 2021. "A co-evolutionary model combined mixed-strategy and network adaptation by severing disassortative neighbors promotes cooperation in prisoner’s dilemma games," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    14. Xiaojie Chen & Attila Szolnoki, 2018. "Punishment and inspection for governing the commons in a feedback-evolving game," PLOS Computational Biology, Public Library of Science, vol. 14(7), pages 1-15, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Du, Faqi & Fu, Feng, 2013. "Quantifying the impact of noise on macroscopic organization of cooperation in spatial games," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 35-44.
    2. 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.
    3. Du, Jinming & Wu, Ziren, 2023. "Coevolutionary dynamics of strategy and network structure with publicity mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 623(C).
    4. Yang, Zhihu & Li, Zhi & Wang, Long, 2020. "Evolution of cooperation in a conformity-driven evolving dynamic social network," Applied Mathematics and Computation, Elsevier, vol. 379(C).
    5. Faqi Du & Feng Fu, 2011. "Partner Selection Shapes the Strategic and Topological Evolution of Cooperation," Dynamic Games and Applications, Springer, vol. 1(3), pages 354-369, September.
    6. Michael Foley & Rory Smead & Patrick Forber & Christoph Riedl, 2021. "Avoiding the bullies: The resilience of cooperation among unequals," PLOS Computational Biology, Public Library of Science, vol. 17(4), pages 1-18, April.
    7. Yu, Fengyuan & Wang, Jianwei & Chen, Wei & He, Jialu, 2023. "Increased cooperation potential and risk under suppressed strategy differentiation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 621(C).
    8. Tian, Yue & Gao, Shun & Li, Haihong & Dai, Qionglin & Yang, Junzhong, 2024. "Particle swarm intelligence promotes cooperation by adapting interaction radii in co-evolutionary games," Applied Mathematics and Computation, Elsevier, vol. 474(C).
    9. Chunyan Zhang & Jianlei Zhang & Guangming Xie & Long Wang & Matjaž Perc, 2011. "Evolution of Interactions and Cooperation in the Spatial Prisoner's Dilemma Game," PLOS ONE, Public Library of Science, vol. 6(10), pages 1-7, October.
    10. Bai, Pengzhou & Qiang, Bingzhuang & Zou, Kuan & Huang, Changwei, 2024. "Preferential selection based on adaptive attractiveness induce by reinforcement learning promotes cooperation," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    11. Mastrandrea, Rossana & Boncinelli, Leonardo & Bilancini, Ennio, 2024. "Coevolution of cognition and cooperation in structured populations under reinforcement learning," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    12. Yang, Guoli & Zhu, Cheng & Zhang, Weiming, 2019. "Adaptive and probabilistic strategy evolution in dynamical networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 518(C), pages 99-110.
    13. Chen, Wei & Wu, Te & Li, Zhiwu & Wang, Long, 2016. "Friendship-based partner switching promotes cooperation in heterogeneous populations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 192-199.
    14. Takesue, Hirofumi, 2021. "Symmetry breaking in the prisoner’s dilemma on two-layer dynamic multiplex networks," Applied Mathematics and Computation, Elsevier, vol. 388(C).
    15. 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).
    16. 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.
    17. Li, Guangyu & Du, Haifeng & He, Xiaochen, 2024. "The evolutionary prisoner’s dilemma game in continuous signed networks," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    18. Du, Jinming & Wu, Ziren, 2022. "Evolutionary dynamics of cooperation in dynamic networked systems with active striving mechanism," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    19. Te Wu & Feng Fu & Long Wang, 2011. "Moving Away from Nasty Encounters Enhances Cooperation in Ecological Prisoner's Dilemma Game," PLOS ONE, Public Library of Science, vol. 6(11), pages 1-7, November.
    20. Ping Zhu & Guiyi Wei, 2014. "Stochastic Heterogeneous Interaction Promotes Cooperation in Spatial Prisoner's Dilemma Game," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-10, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:617:y:2023:i:c:s0378437123002443. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.