IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0317923.html
   My bibliography  Save this article

Evolutionary game on mutually influenceing double-layer network

Author

Listed:
  • Qinzhi Hao
  • Haochun Yang
  • Yao Sun
  • Tao Xu
  • Huang Huang

Abstract

In recent years, coupled double-layer networks have played an increasingly critical role in evolutionary game theory. Research indicates that these networks more accurately reflect real-world relationships between individuals. However, current studies mainly focus on unidirectional influence within double-layer networks. Based on this, we propose a strongly coupled double-layer network cooperation evolution model. Strength individuals are located in the upper network layer, influencing the strategy choices of ordinary individuals in the lower layer, and vice versa. Monte Carlo simulations show that strength individuals can effectively enhance overall group cooperation. Under low temptation to defect, the group maintains a high cooperation rate; under high temptation, the presence of strength individuals prevents the group from falling into total defection, helping ordinary individuals escape the defection dilemma and improve cooperation levels.

Suggested Citation

  • Qinzhi Hao & Haochun Yang & Yao Sun & Tao Xu & Huang Huang, 2025. "Evolutionary game on mutually influenceing double-layer network," PLOS ONE, Public Library of Science, vol. 20(1), pages 1-11, January.
    • Handle: RePEc:plo:pone00:0317923
    DOI: 10.1371/journal.pone.0317923
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0317923
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0317923&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0317923?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
    ---><---

    References listed on IDEAS

    as
    1. Li, Xiaopeng & Hao, Gang & Zhang, Zhipeng & Xia, Chengyi, 2021. "Evolution of cooperation in heterogeneously stochastic interactions," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    2. Ritzberger, Klaus & Weibull, Jorgen W, 1995. "Evolutionary Selection in Normal-Form Games," Econometrica, Econometric Society, vol. 63(6), pages 1371-1399, November.
    3. Huang, Changwei & Han, Wenchen & Li, Haihong & Cheng, Hongyan & Dai, Qionglin & Yang, Junzhong, 2019. "Public cooperation in two-layer networks with asymmetric interaction and learning environments," Applied Mathematics and Computation, Elsevier, vol. 340(C), pages 305-313.
    4. Wang, Chaoqian & Sun, Chengbin, 2023. "Public goods game across multilayer populations with different densities," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    5. Wettergren, Thomas A., 2021. "Replicator dynamics of an N-player snowdrift game with delayed payoffs," Applied Mathematics and Computation, Elsevier, vol. 404(C).
    6. Li, Xiaopeng & Wang, Zhonglin & Xu, Yan & Zhang, Hui & Yu, Guihai, 2024. "Asymmetrical interactions driven by strategic persistence effectively alleviate social dilemmas," Chaos, Solitons & Fractals, Elsevier, vol. 184(C).
    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. Zhou, Meng & Yang, Yanlong & Xiang, Shuwen, 2025. "Effect of community learning mechanism on cooperation in conflict societies," Chaos, Solitons & Fractals, Elsevier, vol. 192(C).
    2. Xiong, Xiaojin & Yao, Yichao & Feng, Minyu & Chica, Manuel, 2024. "Adaptive payoff-driven interaction in networked snowdrift games," Chaos, Solitons & Fractals, Elsevier, vol. 185(C).
    3. Li, Dandan & Wu, Qiongzi & Han, Dun, 2025. "On evolution of agent behavior under limited gaming time with reinforcement learning," Chaos, Solitons & Fractals, Elsevier, vol. 194(C).
    4. Xu, Yan & Zhao, Dawei & Chen, Jiaxing & Liu, Tao & Xia, Chengyi, 2024. "The nested structures of higher-order interactions promote the cooperation in complex social networks," Chaos, Solitons & Fractals, Elsevier, vol. 185(C).
    5. Ling, Ting & Li, Zhang & Feng, Minyu & Szolnoki, Attila, 2025. "Supervised cooperation on interdependent public goods games," Applied Mathematics and Computation, Elsevier, vol. 492(C).
    6. You, Tao & Yang, Haochun & Wang, Jian & Zhang, Peng & Chen, Jinchao & Zhang, Ying, 2023. "Cooperative behavior under the influence of multiple experienced guiders in Prisoner’s dilemma game," Applied Mathematics and Computation, Elsevier, vol. 458(C).
    7. Han, Weiwei & Zhang, Zhipeng & Sun, Junqing & Xia, Chengyi, 2022. "Role of reputation constraints in the spatial public goods game with second-order reputation evaluation," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    8. Sharma, Gopal & He, Zhixue & Shen, Chen & Tanimoto, Jun, 2024. "Asymmetric population promotes and jeopardizes cooperation in spatial prisoner’s dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 187(C).
    9. Shi, Zhenyu & Wei, Wei & Zheng, Hongwei & Zheng, Zhiming, 2023. "Bidirectional supervision: An effective method to suppress corruption and defection under the third party punishment mechanism of donation games," Applied Mathematics and Computation, Elsevier, vol. 450(C).
    10. Guo, Shiqiang & Wang, Juan & Zhao, Dawei & Xia, Chengyi, 2023. "Role of second-order reputation evaluation in the multi-player snowdrift game on scale-free simplicial complexes," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    11. Ianni, A., 2002. "Reinforcement learning and the power law of practice: some analytical results," Discussion Paper Series In Economics And Econometrics 203, Economics Division, School of Social Sciences, University of Southampton.
    12. Tao Du & Jinyu Li & Liuyuanyuan Guo & Xiaohu Wang & Qiuyue Zhu, 2024. "The evolutionary game of establishing a remote consultation system based on the downward allocation of medical resources in a medical alliance," PLOS ONE, Public Library of Science, vol. 19(7), pages 1-25, July.
    13. Zhou, Chen & Zhu, Yuying & Zhao, Dawei & Xia, Chengyi, 2024. "An evolutionary trust game model with group reputation within the asymmetric population," Chaos, Solitons & Fractals, Elsevier, vol. 184(C).
    14. Sandholm,W.H., 2003. "Excess payoff dynamics, potential dynamics, and stable games," Working papers 5, Wisconsin Madison - Social Systems.
    15. Viossat, Yannick, 2008. "Evolutionary dynamics may eliminate all strategies used in correlated equilibrium," Mathematical Social Sciences, Elsevier, vol. 56(1), pages 27-43, July.
    16. Hui Yu & Wei Wang & Baohua Yang & Cunfang Li, 2019. "Evolutionary Game Analysis of the Stress Effect of Cross-Regional Transfer of Resource-Exhausted Enterprises," Complexity, Hindawi, vol. 2019, pages 1-16, November.
    17. Daozhi Zhao & Jiaqin Hao & Cejun Cao & Hongshuai Han, 2019. "Evolutionary Game Analysis of Three-Player for Low-Carbon Production Capacity Sharing," Sustainability, MDPI, vol. 11(11), pages 1-20, May.
    18. Qipeng Sun & Yuqi He & Yongjie Wang & Fei Ma, 2019. "Evolutionary Game between Government and Ride-Hailing Platform: Evidence from China," Discrete Dynamics in Nature and Society, Hindawi, vol. 2019, pages 1-14, January.
    19. Aradhana Narang & A. J. Shaiju, 2019. "Evolutionary Stability of Polymorphic Profiles in Asymmetric Games," Dynamic Games and Applications, Springer, vol. 9(4), pages 1126-1142, December.
    20. Wei Wang & Yanbin Li & Jinzhong Li & Yun Li, 2024. "Can pumped-storage power stations stimulate rural revitalization? Evidence from the four-party evolutionary game," Journal of Evolutionary Economics, Springer, vol. 34(3), pages 595-645, July.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0317923. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.