IDEAS home Printed from https://ideas.repec.org/a/spr/dyngam/v11y2021i1d10.1007_s13235-020-00352-1.html
   My bibliography  Save this article

Costly Participation and The Evolution of Cooperation in the Repeated Public Goods Game

Author

Listed:
  • Xiaofeng Wang

    (Donghua University
    Engineering Research Center of Digitized Textile and Apparel Technology, Donghua University, Ministry of Education)

Abstract

In real life, individuals often need to pay some costs to build and maintain long-termed relationships as well as interactions among them. However, previous studies of the repeated public goods game have focused almost exclusively on the cost-free participation. Here we introduce costly participation to the repeated public goods game in a conditional manner, and study the evolution of cooperation in both deterministic and stochastic dynamics for well-mixed populations. In the limit of an infinite population size, the deterministic dynamics can lead to either a stable coexistence between cooperators and defectors or even a complete dominance of cooperators over defectors if the initial frequency of cooperators is larger than some invasion barrier. In general, defectors are always able to resist invasion by cooperators. However, in finite populations, we show that natural selection can favor the emergence of cooperation in the stochastic dynamics. In the limit of weak selection and large populations, we derive a critical condition required for a cooperator to replace a population of defectors with a selective advantage by using several approximation techniques. Theoretical analysis of the critical condition reveals that participation cost determines the impacts of the number of game round in the emergence of cooperation. Interestingly, there exists an intermediate value of the participation threshold of cooperators leading to the optimal condition for a cooperator to invade and fixate in a population of defectors if the participation cost is smaller than a critical value. Numerical calculations confirm that the validity of the analytical approximations extends to much wider ranges of the selection strength as well as of the population size.

Suggested Citation

  • Xiaofeng Wang, 2021. "Costly Participation and The Evolution of Cooperation in the Repeated Public Goods Game," Dynamic Games and Applications, Springer, vol. 11(1), pages 161-183, March.
  • Handle: RePEc:spr:dyngam:v:11:y:2021:i:1:d:10.1007_s13235-020-00352-1
    DOI: 10.1007/s13235-020-00352-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13235-020-00352-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s13235-020-00352-1?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. Takahiro Ezaki & Yutaka Horita & Masanori Takezawa & Naoki Masuda, 2016. "Reinforcement Learning Explains Conditional Cooperation and Its Moody Cousin," PLOS Computational Biology, Public Library of Science, vol. 12(7), pages 1-13, July.
    2. Francisco C. Santos & Marta D. Santos & Jorge M. Pacheco, 2008. "Social diversity promotes the emergence of cooperation in public goods games," Nature, Nature, vol. 454(7201), pages 213-216, July.
    3. Rand, David Gertler & Dreber, Anna & Fudenberg, Drew & Ellingson, Tore & Nowak, Martin A., 2009. "Positive Interactions Promote Public Cooperation," Scholarly Articles 3804483, Harvard University Department of Economics.
    4. Tanimoto, Jun & Yamauchi, Atsuo, 2010. "Does “game participation cost” affect the advantage of heterogeneous networks for evolving cooperation?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(11), pages 2284-2289.
    5. Martin A. Nowak & Akira Sasaki & Christine Taylor & Drew Fudenberg, 2004. "Emergence of cooperation and evolutionary stability in finite populations," Nature, Nature, vol. 428(6983), pages 646-650, April.
    6. Christian Hilbe & Krishnendu Chatterjee & Martin A. Nowak, 2018. "Partners and rivals in direct reciprocity," Nature Human Behaviour, Nature, vol. 2(7), pages 469-477, July.
    7. 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.
    8. Alexander G. Ginsberg & Feng Fu, 2018. "Evolution of Cooperation in Public Goods Games with Stochastic Opting-Out," Games, MDPI, vol. 10(1), pages 1-27, December.
    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. Pi, Jinxiu & Yang, Guanghui & Tang, Wei & Yang, Hui, 2022. "Stochastically stable equilibria for evolutionary snowdrift games with time costs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    2. Xu, Yan & Feng, Meiling & Zhu, Yuying & Xia, Chengyi, 2022. "Multi-player snowdrift game on scale-free simplicial complexes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    3. Gao, Shiping & Li, Nan, 2023. "Preference reversal and the evolution of cooperation," Applied Mathematics and Computation, Elsevier, vol. 438(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. Wang, Mie & Kang, HongWei & Shen, Yong & Sun, XingPing & Chen, QingYi, 2021. "The role of alliance cooperation in spatial public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 152(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. Mohammad Salahshour, 2021. "Freedom to choose between public resources promotes cooperation," PLOS Computational Biology, Public Library of Science, vol. 17(2), pages 1-15, February.
    4. Shuhua Chang & Zhipeng Zhang & Yu Li & Yu E Wu & Yunya Xie, 2018. "Investment preference promotes cooperation in spatial public goods game," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-14, November.
    5. Ma, Xiaojian & Quan, Ji & Wang, Xianjia, 2023. "Evolution of cooperation with nonlinear environment feedback in repeated public goods game," Applied Mathematics and Computation, Elsevier, vol. 452(C).
    6. Dario Madeo & Chiara Mocenni, 2021. "Consensus towards Partially Cooperative Strategies in Self-Regulated Evolutionary Games on Networks," Games, MDPI, vol. 12(3), pages 1-16, July.
    7. Maria Kleshnina & Christian Hilbe & Štěpán Šimsa & Krishnendu Chatterjee & Martin A. Nowak, 2023. "The effect of environmental information on evolution of cooperation in stochastic games," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    8. Dario Madeo & Chiara Mocenni, 2018. "Self-regulation promotes cooperation in social networks," Papers 1807.07848, arXiv.org.
    9. Du, Faqi & Fu, Feng, 2013. "Quantifying the impact of noise on macroscopic organization of cooperation in spatial games," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 35-44.
    10. Huang, Keke & Liu, Yishun & Zhang, Yichi & Yang, Chunhua & Wang, Zhen, 2018. "Understanding cooperative behavior of agents with heterogeneous perceptions in dynamic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 234-240.
    11. 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.
    12. Huang, Keke & Zheng, Xiaoping & Yang, Yeqing & Wang, Tao, 2015. "Behavioral evolution in evacuation crowd based on heterogeneous rationality of small groups," Applied Mathematics and Computation, Elsevier, vol. 266(C), pages 501-506.
    13. Dimitris Iliopoulos & Arend Hintze & Christoph Adami, 2010. "Critical Dynamics in the Evolution of Stochastic Strategies for the Iterated Prisoner's Dilemma," PLOS Computational Biology, Public Library of Science, vol. 6(10), pages 1-8, October.
    14. 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).
    15. Wang, Zhen & Chen, Tong & Wang, Yongjie, 2017. "Leadership by example promotes the emergence of cooperation in public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 101(C), pages 100-105.
    16. Tetsushi Ohdaira, 2021. "Cooperation evolves by the payoff-difference-based probabilistic reward," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(11), pages 1-8, November.
    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. Zhuang, Qian & Wang, Dong & Fan, Ying & Di, Zengru, 2012. "Evolution of cooperation in a heterogeneous population with influential individuals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1735-1741.
    19. Chen, Qiao & Chen, Tong & Wang, Yongjie, 2017. "Publishing the donation list incompletely promotes the emergence of cooperation in public goods game," Applied Mathematics and Computation, Elsevier, vol. 310(C), pages 48-56.
    20. Li, Jing & Wang, Jiang, 2018. "Locality based wealth rule favors cooperation in costly public goods games," Chaos, Solitons & Fractals, Elsevier, vol. 116(C), pages 1-7.

    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:spr:dyngam:v:11:y:2021:i:1:d:10.1007_s13235-020-00352-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.