IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v121y2019icp59-62.html
   My bibliography  Save this article

An adaptive replacement of the rule update triggers the cooperative evolution in the Hawk–Dove game

Author

Listed:
  • Sakiyama, Tomoko
  • Arizono, Ikuo

Abstract

Since Maynard Smith and Price proposed the earliest version of Hawk–Dove (HD) game, it attracted researchers’ attention as one of models of conflict for two players in game theory. In conflict game, the players’ benefit depends on the strategy of opponent for each other. In the classical spatial HD games, if one player adopts defector strategy, it tends to get high payoffs, and therefore increases population of the same strategy, which resulting in an extinction of cooperators. Several studies tried to solve the problem of an extinction of cooperator in spatial HD game. In this paper, we developed a novel spatial HD model replacing the best takes over update rule with different one, and investigated the effect of modifying update rules on the problem of collaborators extinction in space HD games. We found that our model generated characteristic population patterns and represented the survival of cooperators compared with the classical spatial HD model in which the updated rule was fixed.

Suggested Citation

  • Sakiyama, Tomoko & Arizono, Ikuo, 2019. "An adaptive replacement of the rule update triggers the cooperative evolution in the Hawk–Dove game," Chaos, Solitons & Fractals, Elsevier, vol. 121(C), pages 59-62.
    • Handle: RePEc:eee:chsofr:v:121:y:2019:i:c:p:59-62
    DOI: 10.1016/j.chaos.2019.01.014
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077918308208
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2019.01.014?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. Christoph Hauert & Michael Doebeli, 2004. "Spatial structure often inhibits the evolution of cooperation in the snowdrift game," Nature, Nature, vol. 428(6983), pages 643-646, April.
    2. Li, Yumeng & Zhang, Jun & Perc, Matjaž, 2018. "Effects of compassion on the evolution of cooperation in spatial social dilemmas," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 437-443.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sakiyama, Tomoko, 2021. "A power law network in an evolutionary hawk–dove game," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    2. Takahara, Akihiro & Sakiyama, Tomoko, 2023. "Twisted strategy may enhance the evolution of cooperation in spatial prisoner’s dilemma," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    3. Bin, Liu & Yue, Wu, 2023. "Co-evolution of reputation-based preference selection and resource allocation with multigame on interdependent networks," Applied Mathematics and Computation, Elsevier, vol. 456(C).

    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. Yang, Zhengzhi & Zheng, Lei & Perc, Matjaž & Li, Yumeng, 2024. "Interaction state Q-learning promotes cooperation in the spatial prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 463(C).
    2. Chen, Qiao & Chen, Tong & Wang, Yongjie, 2019. "Cleverly handling the donation information can promote cooperation in public goods game," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 363-373.
    3. 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).
    4. Dong, Yukun & Xu, Hedong & Fan, Suohai, 2019. "Memory-based stag hunt game on regular lattices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 247-255.
    5. Li, Yumeng & Wang, Hanchen & Du, Wenbo & Perc, Matjaž & Cao, Xianbin & Zhang, Jun, 2019. "Resonance-like cooperation due to transaction costs in the prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 248-257.
    6. Takahara, Akihiro & Sakiyama, Tomoko, 2023. "Twisted strategy may enhance the evolution of cooperation in spatial prisoner’s dilemma," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    7. Jorge Peña & Yannick Rochat, 2012. "Bipartite Graphs as Models of Population Structures in Evolutionary Multiplayer Games," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-13, September.
    8. 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.
    9. Qinghu Liao & Wenwen Dong & Boxin Zhao, 2023. "A New Strategy to Solve “the Tragedy of the Commons” in Sustainable Grassland Ecological Compensation: Experience from Inner Mongolia, China," Sustainability, MDPI, vol. 15(12), pages 1-24, June.
    10. Lv, Shaojie & Wang, Xianjia, 2020. "The impact of heterogeneous investments on the evolution of cooperation in public goods game with exclusion," Applied Mathematics and Computation, Elsevier, vol. 372(C).
    11. Zhao, Zhengwu & Zhang, Chunyan, 2023. "The mechanisms of labor division from the perspective of task urgency and game theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    12. Hu, Menglong & Wang, Juan & Kong, Lingcong & An, Kang & Bi, Tao & Guo, Baohong & Dong, Enzeng, 2015. "Incorporating the information from direct and indirect neighbors into fitness evaluation enhances the cooperation in the social dilemmas," Chaos, Solitons & Fractals, Elsevier, vol. 77(C), pages 47-52.
    13. Bin Wu & Julián García & Christoph Hauert & Arne Traulsen, 2013. "Extrapolating Weak Selection in Evolutionary Games," PLOS Computational Biology, Public Library of Science, vol. 9(12), pages 1-7, December.
    14. Cheng, Yuan & Chang, Meng & Xue, Yanbo, 2020. "A computational study of promotion dynamics and organizational efficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    15. Chen, Wei & Wang, Jianwei & Yu, Fengyuan & He, Jialu & Xu, Wenshu & Dai, Wenhui, 2024. "Successful initial positioning of non-cooperative individuals in cooperative populations effectively hinders cooperation prosperity," Applied Mathematics and Computation, Elsevier, vol. 462(C).
    16. Jin, Jiahua & Shen, Chen & Chu, Chen & Shi, Lei, 2017. "Incorporating dominant environment into individual fitness promotes cooperation in the spatial prisoners' dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 96(C), pages 70-75.
    17. Zhang, Lan & Huang, Changwei, 2023. "Preferential selection to promote cooperation on degree–degree correlation networks in spatial snowdrift games," Applied Mathematics and Computation, Elsevier, vol. 454(C).
    18. Zhang, Hui & Wang, Li & Hou, Dongshuang, 2016. "Effect of the spatial autocorrelation of empty sites on the evolution of cooperation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 296-308.
    19. Fulin Guo, 2023. "Experience-weighted attraction learning in network coordination games," Papers 2310.18835, arXiv.org.
    20. Chunyan Zhang & Jianlei Zhang & Franz J Weissing & Matjaž Perc & Guangming Xie & Long Wang, 2012. "Different Reactions to Adverse Neighborhoods in Games of Cooperation," PLOS ONE, Public Library of Science, vol. 7(4), pages 1-7, 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:chsofr:v:121:y:2019:i:c:p:59-62. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.