IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v413y2022ics0096300321006871.html
   My bibliography  Save this article

The effect of stability-based strategy updating on cooperation in evolutionary social dilemmas

Author

Listed:
  • Zha, Jiajing
  • Li, Cong
  • Fan, Suohai

Abstract

The stability of payoffs, often depicted by variance, provides more information during the decision-making process. With the help of memory, we propose a stability-based strategy updating rule and study its effect on cooperative behaviors. Under this updating rule, the probability of learning strategy is affected not only by the difference of average payoffs but also the stability. Based on the prisoner’s dilemma game and snowdrift game, simulations show that compared with the Fermi rule, the introduction of stability enhances cooperative behaviors and average payoffs. Moreover, cooperators in population own much higher and more stable payoffs than defectors when considering long memories. Compared with the memory-based rule which considers the difference of average payoffs, the stability-based rule shows these superiorities on cooperators when the payoff parameters are relatively large, which suggests that the proposed rule exhibits its dominant position when the fluctuation of payoffs is obvious. According to this conclusion, we obtain the application scope enhancing cooperators of memory-based and stability-based rules, which maybe helpful in understanding the influence of these two rules on cooperation under different circumstances.

Suggested Citation

  • Zha, Jiajing & Li, Cong & Fan, Suohai, 2022. "The effect of stability-based strategy updating on cooperation in evolutionary social dilemmas," Applied Mathematics and Computation, Elsevier, vol. 413(C).
    • Handle: RePEc:eee:apmaco:v:413:y:2022:i:c:s0096300321006871
    DOI: 10.1016/j.amc.2021.126603
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300321006871
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2021.126603?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. Shu, Feng & Liu, Xingwen & Fang, Kai & Chen, Hao, 2018. "Memory-based snowdrift game on a square lattice," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 15-26.
    2. Cao, Xian-Bin & Du, Wen-Bo & Rong, Zhi-Hai, 2010. "The evolutionary public goods game on scale-free networks with heterogeneous investment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(6), pages 1273-1280.
    3. Wang, Chengjiang & Wang, Li & Wang, Juan & Sun, Shiwen & Xia, Chengyi, 2017. "Inferring the reputation enhances the cooperation in the public goods game on interdependent lattices," Applied Mathematics and Computation, Elsevier, vol. 293(C), pages 18-29.
    4. Szolnoki, Attila & Danku, Zsuzsa, 2018. "Dynamic-sensitive cooperation in the presence of multiple strategy updating rules," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 511(C), pages 371-377.
    5. Blume Lawrence E., 1993. "The Statistical Mechanics of Strategic Interaction," Games and Economic Behavior, Elsevier, vol. 5(3), pages 387-424, July.
    6. 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.
    7. Ye, Wenxing & Feng, Weiying & Lü, Chen & Fan, Suohai, 2017. "Memory-based prisoner’s dilemma game with conditional selection on networks," Applied Mathematics and Computation, Elsevier, vol. 307(C), pages 31-37.
    8. Wang, Qun & Wang, Hanchen & Zhang, Zhuxi & Li, Yumeng & Liu, Yu & Perc, Matjaž, 2018. "Heterogeneous investments promote cooperation in evolutionary public goods games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 570-575.
    9. Wang, Jianwei & Wang, Rong & Yu, Fengyuan & Wang, Ziwei & Li, Qiaochu, 2020. "Learning continuous and consistent strategy promotes cooperation in prisoner’s dilemma game with mixed strategy," Applied Mathematics and Computation, Elsevier, vol. 370(C).
    10. John M. McNamara & Zoltan Barta & Alasdair I. Houston, 2004. "Variation in behaviour promotes cooperation in the Prisoner's Dilemma game," Nature, Nature, vol. 428(6984), pages 745-748, April.
    11. Manfred Milinski & Dirk Semmann & Hans-Jürgen Krambeck, 2002. "Reputation helps solve the ‘tragedy of the commons’," Nature, Nature, vol. 415(6870), pages 424-426, January.
    12. Zhang, Haifeng & Yang, Hanxin & Du, Wenbo & Wang, Binghong & Cao, Xianbin, 2010. "Evolutionary public goods games on scale-free networks with unequal payoff allocation mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(5), pages 1099-1104.
    13. Ye, Wenxing & Fan, Suohai, 2017. "Evolutionary snowdrift game with rational selection based on radical evaluation," Applied Mathematics and Computation, Elsevier, vol. 294(C), pages 310-317.
    14. 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.
    15. Liu, Yongkui & Li, Zhi & Chen, Xiaojie & Wang, Long, 2010. "Memory-based prisoner’s dilemma on square lattices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(12), pages 2390-2396.
    16. Liu, Yongkui & Zhang, Lin & Chen, Xiaojie & Ren, Lei & Wang, Long, 2013. "Cautious strategy update promotes cooperation in spatial prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3640-3647.
    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. Yunsheng Deng & Jihui Zhang, 2022. "The choice-decision based on memory and payoff favors cooperation in stag hunt game on interdependent networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 95(2), pages 1-13, February.
    2. 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.
    3. Li, Cong & Xu, Hedong & Fan, Suohai, 2020. "Synergistic effects of self-optimization and imitation rules on the evolution of cooperation in the investor sharing game," Applied Mathematics and Computation, Elsevier, vol. 370(C).
    4. 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.
    5. Zhu, Jiabao & Liu, Xingwen, 2021. "The number of strategy changes can be used to promote cooperation in spatial snowdrift game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 575(C).
    6. Chen, Wei & Wang, Jianwei & Yu, Fengyuan & He, Jialu & Xu, Wenshu & Wang, Rong, 2021. "Effects of emotion on the evolution of cooperation in a spatial prisoner’s dilemma game," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    7. Zhang, Jing & Li, Zhao & Zhang, Jiqiang & Ma, Lin & Zheng, Guozhong & Chen, Li, 2023. "Emergence of oscillatory cooperation in a population with incomplete information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 617(C).
    8. Shu, Feng & Liu, Yaojun & Liu, Xingwen & Zhou, Xiaobing, 2019. "Memory-based conformity enhances cooperation in social dilemmas," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 480-490.
    9. Wang, Dongqi & Shuai, Xuanyue & Pan, Qiuhui & Li, Jingye & Lan, Xiaolong & He, Mingfeng, 2020. "Long deliberation times promote cooperation in the prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    10. Deng, Yunsheng & Zhang, Jihui, 2021. "The role of the preferred neighbor with the expected payoff on cooperation in spatial public goods game under optimal strategy selection mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).
    11. Duan, Yuxian & Huang, Jian & Zhang, Jiarui, 2023. "Evolutionary public good games based on the long-term payoff mechanism in heterogeneous networks," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    12. 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.
    13. Lu, Wen & Liang, Shu, 2023. "Direct emotional interaction in prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 458(C).
    14. 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).
    15. Sun, Jiaqin & Fan, Ruguo & Luo, Ming & Zhang, Yingqing & Dong, Lili, 2018. "The evolution of cooperation in spatial prisoner’s dilemma game with dynamic relationship-based preferential learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 598-611.
    16. Cheng, Fei & Chen, Tong & Chen, Qiao, 2020. "Rewards based on public loyalty program promote cooperation in public goods game," Applied Mathematics and Computation, Elsevier, vol. 378(C).
    17. 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).
    18. 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.
    19. Li, Jiaqi & Zhang, Jianlei & Chen, Zengqiang & Liu, Qun, 2023. "Aspiration drives adaptive switching between two different payoff matrices," Applied Mathematics and Computation, Elsevier, vol. 446(C).
    20. Pi, Bin & Li, Yuhan & Feng, Minyu, 2022. "An evolutionary game with conformists and profiteers regarding the memory mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 597(C).

    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:413:y:2022:i:c:s0096300321006871. 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.