IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v399y2021ics0096300321000953.html
   My bibliography  Save this article

Effects of defensive cooperation strategy on the evolution of cooperation in social dilemma

Author

Listed:
  • Gao, Liyan
  • Pan, Qiuhui
  • He, Mingfeng

Abstract

Punishment and reward are effective ways to sustain cooperation among selfish groups. Researches show that the ultimate result of selflessness is self-interest. This paper considers that individuals take defensive measures to reduce losses in the face of unknown risks. Defensive cooperators need to pay the defensive cost. When they interact with unconditional defectors, the defensive cooperators gain benefit due to defensive behavior, while the unconditional defectors lose some benefit due to the defense of defensive cooperators. Results show that in the well-mixed population, reducing defensive cost and improving defensive benefit can promote cooperation, and maintain a higher cooperation level unchanged within a larger range of temptation. In the structured population, the three strategies perform the phenomenon of cyclic dominance, that is unconditional cooperators dominate defensive cooperators who dominate unconditional defectors who dominate unconditional cooperators. It is worth noting that both in the well-mixed population and structured population, three strategies have obvious phased advantages with regard to defensive benefit. Lower defensive benefit leads to an advantage for unconditional defectors. If defensive benefit is moderate, the weakened competitiveness of unconditional defectors leads defensive cooperators dominate. And excessive defensive benefit results in the second-order free-rider phenomenon of the unconditional cooperation strategy. In addition, structured population do not always support cooperation better than well-mixed population. When the defensive cost is small and defensive benefit is high, the spatial effect can enhance network reciprocity. More generally, our results prove that defensive self-interested behavior leads to the maintenance of cooperation, which provides a new perspective for understanding the cooperation evolutionary.

Suggested Citation

  • Gao, Liyan & Pan, Qiuhui & He, Mingfeng, 2021. "Effects of defensive cooperation strategy on the evolution of cooperation in social dilemma," Applied Mathematics and Computation, Elsevier, vol. 399(C).
  • Handle: RePEc:eee:apmaco:v:399:y:2021:i:c:s0096300321000953
    DOI: 10.1016/j.amc.2021.126047
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300321000953
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2021.126047?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. Imhof, Lorens & Nowak, Martin & Fudenberg, Drew, 2007. "Tit-for-Tat or Win-Stay, Lose-Shift?," Scholarly Articles 3200671, Harvard University Department of Economics.
    2. Geng, Yini & Shen, Chen & Hu, Kaipeng & Shi, Lei, 2018. "Impact of punishment on the evolution of cooperation in spatial prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 540-545.
    3. Wu, Yu’e & Zhang, Zhipeng & Chang, Shuhua, 2017. "Effect of self-interaction on the evolution of cooperation in complex topologies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 191-197.
    4. Wang, Xu-Wen & Nie, Sen & Jiang, Luo-Luo & Wang, Bing-Hong & Chen, Shi-Ming, 2017. "Role of delay-based reward in the spatial cooperation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 153-158.
    5. Ernst Fehr & Simon Gächter, 2002. "Altruistic punishment in humans," Nature, Nature, vol. 415(6868), pages 137-140, January.
    6. Song, Qun & Cao, Zhaoheng & Tao, Rui & Jiang, Wei & Liu, Chen & Liu, Jinzhuo, 2020. "Conditional neutral punishment promotes cooperation in the spatial prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 368(C).
    7. Wu, Yu’e & Zhang, Zhipeng & Chang, Shuhua, 2019. "Reciprocal reward promotes the evolution of cooperation in structured populations," Chaos, Solitons & Fractals, Elsevier, vol. 119(C), pages 230-236.
    8. Du, Wen-Bo & Zheng, Hao-Ran & Hu, Mao-Bin, 2008. "Evolutionary prisoner’s dilemma game on weighted scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(14), pages 3796-3800.
    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. Zhu, Wenqiang & Pan, Qiuhui & He, Mingfeng, 2022. "Exposure-based reputation mechanism promotes the evolution of cooperation," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    2. Gao, Liyan & Pan, Qiuhui & He, Mingfeng, 2022. "Advanced defensive cooperators promote cooperation in the prisoner’s dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    3. Chen, Qin & Pan, Qiuhui & He, Mingfeng, 2022. "The influence of quasi-cooperative strategy on social dilemma evolution," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    4. 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).
    5. Song, Sha & Pan, Qiuhui & Zhu, Wenqiang & He, Mingfeng, 2023. "Evolution of cooperation in games with dual attribute strategy," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    6. Zhu, Wenqiang & Pan, Qiuhui & Song, Sha & He, Mingfeng, 2023. "Effects of exposure-based reward and punishment on the evolution of cooperation in prisoner’s dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 172(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. Huang, Shaoxu & Liu, Xuesong & Hu, Yuhan & Fu, Xiao, 2023. "The influence of aggressive behavior on cooperation evolution in social dilemma," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    2. Zhenghong Wu & Huan Huang & Qinghu Liao, 2021. "The study on the role of dedicators on promoting cooperation in public goods game," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-17, September.
    3. Chang, Shuhua & Zhang, Zhipeng & Wu, Yu’e & Xie, Yunya, 2018. "Cooperation is enhanced by inhomogeneous inertia in spatial prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 419-425.
    4. Bi, Yan & Yang, Hui, 2023. "Based on reputation consistent strategy times promotes cooperation in spatial prisoner’s dilemma game," Applied Mathematics and Computation, Elsevier, vol. 444(C).
    5. Gao, Liyan & Pan, Qiuhui & He, Mingfeng, 2022. "Advanced defensive cooperators promote cooperation in the prisoner’s dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    6. Zhang, Shuhua & Zhang, Zhipeng & Wu, Yu’e & Yan, Ming & Li, Yu, 2019. "Strategy preference promotes cooperation in spatial evolutionary games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 181-188.
    7. Wu, Yu’e & Zhang, Zhipeng & Chang, Shuhua, 2019. "Reciprocal reward promotes the evolution of cooperation in structured populations," Chaos, Solitons & Fractals, Elsevier, vol. 119(C), pages 230-236.
    8. Swami Iyer & Timothy Killingback, 2020. "Evolution of Cooperation in Social Dilemmas with Assortative Interactions," Games, MDPI, vol. 11(4), pages 1-31, September.
    9. Quan, Ji & Yu, Junyu & Li, Xia & Wang, Xianjia, 2023. "Conditional switching between social excluders and loners promotes cooperation in spatial public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    10. Wu, Yu’e & Zhang, Zhipeng & Wang, Xinyu & Chang, Shuhua, 2019. "Impact of probabilistic incentives on the evolution of cooperation in complex topologies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 307-314.
    11. Li, Cong & Xu, Hedong & Fan, Suohai, 2021. "Evolutionary compromise game on assortative mixing networks," Applied Mathematics and Computation, Elsevier, vol. 390(C).
    12. Pan, Qiuhui & Wang, Linpeng & He, Mingfeng, 2020. "Social dilemma based on reputation and successive behavior," Applied Mathematics and Computation, Elsevier, vol. 384(C).
    13. Zhang, Xiaoyang & Chen, Tong & Chen, Qiao & Li, Xueya, 2020. "Increasing pool funds in public goods: The effects of deposit-based delayed rewards," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    14. Feng, Sinan & Liu, Xuesong, 2023. "Effects of the limited incentive pool on cooperation evolution in public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    15. Flávio L Pinheiro & Vítor V Vasconcelos & Francisco C Santos & Jorge M Pacheco, 2014. "Evolution of All-or-None Strategies in Repeated Public Goods Dilemmas," PLOS Computational Biology, Public Library of Science, vol. 10(11), pages 1-5, November.
    16. Gao, Liyan & Pan, Qiuhui & He, Mingfeng, 2021. "Environmental-based defensive promotes cooperation in the prisoner’s dilemma game," Applied Mathematics and Computation, Elsevier, vol. 401(C).
    17. 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).
    18. Checchi, Daniele & Visser, Jelle & van de Werfhorst, Herman G., 2007. "Inequality and Union Membership: The Impact of Relative Earnings Position and Inequality Attitudes," IZA Discussion Papers 2691, Institute of Labor Economics (IZA).
    19. Carlo Borzaga & Ermanno Tortia, 2004. "Worker involvement in entrepreneurial nonprofit organizations. Toward a new assessment of workers' perceived satisfaction and fairness," Department of Economics Working Papers 0409, Department of Economics, University of Trento, Italia.
    20. Christoph Engel & Michael Kurschilgen, 2011. "Fairness Ex Ante and Ex Post: Experimentally Testing Ex Post Judicial Intervention into Blockbuster Deals," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 8(4), pages 682-708, December.

    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:399:y:2021:i:c:s0096300321000953. 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.