IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v456y2023ics009630032300303x.html
   My bibliography  Save this article

Evolutionary cooperation dynamics of combining imitation and super-rational aspiration induced strategy updating

Author

Listed:
  • Wang, Si-Yi
  • Wang, Qing-Lian
  • Zhang, Xiao-Wei
  • Wang, Rui-Wu

Abstract

In evolutionary game theory, strategy updating plays an important role in the evolution of cooperation, mainly including the Moran process, imitation, aspiration-driven updating, and super-rational aspiration induced strategy updating. Previous studies have focused on a single strategy updating but ignored the impact of environmental stochasticity and individual preference. In this paper, we study the evolutionary cooperation dynamics combining imitation and super-rational aspiration induced strategy updating in well-mixed finite populations. That is, individuals can no longer use a single update, but can choose to use imitation updating or super-rational aspiration induced strategy updating (i.e. mixed strategy updating). The closed-form expression of the fixation probability under arbitrary selection intensity is given, the approximate expression of the cooperation fixation probability is given, and the parameters favorable to cooperation fixation are given. The results show that cooperation is promoted when the cooperator is super-rational and inhibited when the defector is super-rational. This conclusion is verified by the approximate results of the mean-field theory and the simulation results in the structured population. In addition, the evolution of cooperation is given in two cases: the cooperator is completely super-rational but the defector is not super-rational, and the cooperator is not super-rational but the defector is completely super-rational. These results provide new perspectives on the evolution of cooperation.

Suggested Citation

  • Wang, Si-Yi & Wang, Qing-Lian & Zhang, Xiao-Wei & Wang, Rui-Wu, 2023. "Evolutionary cooperation dynamics of combining imitation and super-rational aspiration induced strategy updating," Applied Mathematics and Computation, Elsevier, vol. 456(C).
  • Handle: RePEc:eee:apmaco:v:456:y:2023:i:c:s009630032300303x
    DOI: 10.1016/j.amc.2023.128134
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S009630032300303X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2023.128134?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. Matjaž Perc & Zhen Wang, 2010. "Heterogeneous Aspirations Promote Cooperation in the Prisoner's Dilemma Game," PLOS ONE, Public Library of Science, vol. 5(12), pages 1-8, December.
    2. Du, Chunpeng & Guo, Keyu & Lu, Yikang & Jin, Haoyu & Shi, Lei, 2023. "Aspiration driven exit-option resolves social dilemmas in the network," Applied Mathematics and Computation, Elsevier, vol. 438(C).
    3. Lv, Shaojie & Zhao, Changheng & Li, Jiaying, 2022. "Generosity in public goods game with the aspiration-driven rule," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    4. 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.
    5. Lin, Jingyan & Huang, Changwei & Dai, Qionglin & Yang, Junzhong, 2020. "Evolutionary game dynamics of combining the payoff-driven and conformity-driven update rules," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    6. Zhang, Jun & Fang, Yi-Ping & Du, Wen-Bo & Cao, Xian-Bin, 2011. "Promotion of cooperation in aspiration-based spatial prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(12), pages 2258-2266.
    7. Hong, Lijun & Geng, Yini & Du, Chunpeng & Shen, Chen & Shi, Lei, 2021. "Average payoff-driven or imitation? A new evidence from evolutionary game theory in finite populations," Applied Mathematics and Computation, Elsevier, vol. 394(C).
    8. Shu, Gang & Du, Xia & Li, Ya, 2016. "Surrounding information consideration promotes cooperation in Prisoner’s dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 689-694.
    9. 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.
    10. Wang, Si-Yi & Feng, Tian-Jiao & Tao, Yi & Wu, Jia-Jia, 2023. "Impact of individual sensitivity to payoff difference between individuals on a discrete-time imitation dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    11. Liu, Xuesong & He, Mingfeng & Kang, Yibin & Pan, Qiuhui, 2017. "Fixation of strategies with the Moran and Fermi processes in evolutionary games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 336-344.
    12. Rankin, Frederick W. & Van Huyck, John B. & Battalio, Raymond C., 2000. "Strategic Similarity and Emergent Conventions: Evidence from Similar Stag Hunt Games," Games and Economic Behavior, Elsevier, vol. 32(2), pages 315-337, August.
    13. Wang, Si-Yi & Liu, Yan-Ping & Zhang, Feng & Wang, Rui-Wu, 2021. "Super-rational aspiration induced strategy updating promotes cooperation in the asymmetric prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 403(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. He, Jialu & Wang, Jianwei & Yu, Fengyuan & Chen, Wei & Li, Bofan, 2022. "The slow but persistent self-improvement boosts group cooperation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    2. Wang, Si-Yi & Liu, Yan-Ping & Zhang, Feng & Wang, Rui-Wu, 2021. "Super-rational aspiration induced strategy updating promotes cooperation in the asymmetric prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 403(C).
    3. Flávio L Pinheiro & Jorge M Pacheco & Francisco C Santos, 2012. "From Local to Global Dilemmas in Social Networks," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-6, February.
    4. Li, Xiaopeng & Hao, Gang & Zhang, Zhipeng & Xia, Chengyi, 2021. "Evolution of cooperation in heterogeneously stochastic interactions," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    5. Keizo Shigaki & Zhen Wang & Jun Tanimoto & Eriko Fukuda, 2013. "Effect of Initial Fraction of Cooperators on Cooperative Behavior in Evolutionary Prisoner's Dilemma Game," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-7, November.
    6. 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.
    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. 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).
    10. 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.
    11. Han, Jia-Xu & Wang, Rui-Wu, 2023. "Complex interactions promote the frequency of cooperation in snowdrift game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    12. Xia, Ke, 2021. "The characteristics of average abundance function of multi-player threshold public goods evolutionary game model under redistribution mechanism," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    13. Qiguang An & Hongfeng Guo & Yating Zheng, 2022. "On Robust Stability and Stabilization of Networked Evolutionary Games with Time Delays," Mathematics, MDPI, vol. 10(15), pages 1-12, July.
    14. Sabin Lessard, 2011. "Effective Game Matrix and Inclusive Payoff in Group-Structured Populations," Dynamic Games and Applications, Springer, vol. 1(2), pages 301-318, June.
    15. Chen, Qin & Pan, Qiuhui & He, Mingfeng, 2022. "The influence of quasi-cooperative strategy on social dilemma evolution," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    16. Quan, Ji & Zhou, Yawen & Wang, Xianjia & Yang, Jian-Bo, 2020. "Information fusion based on reputation and payoff promotes cooperation in spatial public goods game," Applied Mathematics and Computation, Elsevier, vol. 368(C).
    17. Hong, Lijun & Geng, Yini & Du, Chunpeng & Shen, Chen & Shi, Lei, 2021. "Average payoff-driven or imitation? A new evidence from evolutionary game theory in finite populations," Applied Mathematics and Computation, Elsevier, vol. 394(C).
    18. Jin, Jiahua & Chu, Chen & Shen, Chen & Guo, Hao & Geng, Yini & Jia, Danyang & Shi, Lei, 2018. "Heterogeneous fitness promotes cooperation in the spatial prisoner's dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 141-146.
    19. Yongkui Liu & Xiaojie Chen & Lin Zhang & Long Wang & Matjaž Perc, 2012. "Win-Stay-Lose-Learn Promotes Cooperation in the Spatial Prisoner's Dilemma Game," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-8, February.
    20. Lefeng Cheng & Pan Peng & Wentian Lu & Pengrong Huang & Yang Chen, 2024. "Study of Flexibility Transformation in Thermal Power Enterprises under Multi-Factor Drivers: Application of Complex-Network Evolutionary Game Theory," Mathematics, MDPI, vol. 12(16), pages 1-23, August.

    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:eee:apmaco:v:456:y:2023:i:c:s009630032300303x. 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: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.