IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v467y2017icp499-507.html
   My bibliography  Save this article

The maintenance of cooperation in multiplex networks with limited and partible resources of agents

Author

Listed:
  • Li, Zhaofeng
  • Shen, Bi
  • Jiang, Yichuan

Abstract

In this paper, we try to explain the maintenance of cooperation in multiplex networks with limited and partible resources of agents: defection brings larger short-term benefit and cooperative agents may become defective because of the unaffordable costs of cooperative behaviors that are performed in multiple layers simultaneously. Recent studies have identified the positive effects of multiple layers on evolutionary cooperation but generally overlook the maximum costs of agents in these synchronous games. By utilizing network effects and designing evolutionary mechanisms, cooperative behaviors become prevailing in public goods games, and agents can allocate personal resources across multiple layers. First, we generalize degree diversity into multiplex networks to improve the prospect for cooperation. Second, to prevent agents allocating all the resources into one layer, a greedy-first mechanism is proposed, in which agents prefer to add additional investments in the higher-payoff layer. It is found that greedy-first agents can perform cooperative behaviors in multiplex networks when one layer is scale-free network and degree differences between conjoint nodes increase. Our work may help to explain the emergence of cooperation in the absence of individual reputation and punishment mechanisms.

Suggested Citation

  • Li, Zhaofeng & Shen, Bi & Jiang, Yichuan, 2017. "The maintenance of cooperation in multiplex networks with limited and partible resources of agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 499-507.
    • Handle: RePEc:eee:phsmap:v:467:y:2017:i:c:p:499-507
    DOI: 10.1016/j.physa.2016.10.040
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437116307270
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2016.10.040?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. 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.
    2. 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.
    3. Gomez Portillo, Ignacio, 2014. "Cooperative networks overcoming defectors by social influence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 198-210.
    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. A. B. Leoneti & G. A. Prataviera, 2020. "Entropy-Norm space for geometric selection of strict Nash equilibria in n-person games," Papers 2003.09225, arXiv.org.
    2. Leoneti, A.B. & Prataviera, G.A., 2020. "Entropy-norm space for geometric selection of strict Nash equilibria in n-person games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 546(C).
    3. Quan, Ji & Yang, Xiukang & Wang, Xianjia, 2018. "Spatial public goods game with continuous contributions based on Particle Swarm Optimization learning and the evolution of cooperation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 973-983.

    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. 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.
    2. 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.
    3. D. Timothy Bishop & Mark Broom & Richard Southwell, 2020. "Chris Cannings: A Life in Games," Dynamic Games and Applications, Springer, vol. 10(3), pages 591-617, September.
    4. Chen, Wei & Zhu, Qianlong & Wu, Te, 2023. "Unfairness promotes the evolution of cooperation," Applied Mathematics and Computation, Elsevier, vol. 438(C).
    5. Spiekermann, Kai, 2009. "Sort out your neighbourhood: public good games on dynamic networks," LSE Research Online Documents on Economics 26739, London School of Economics and Political Science, LSE Library.
    6. 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.
    7. Fabio Della Rossa & Fabio Dercole & Anna Di Meglio, 2020. "Direct Reciprocity and Model-Predictive Strategy Update Explain the Network Reciprocity Observed in Socioeconomic Networks," Games, MDPI, vol. 11(1), pages 1-28, March.
    8. Sarkar, Bijan, 2021. "The cooperation–defection evolution on social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).
    9. Qi Su & Lei Zhou & Long Wang, 2019. "Evolutionary multiplayer games on graphs with edge diversity," PLOS Computational Biology, Public Library of Science, vol. 15(4), pages 1-22, April.
    10. Yu, Jianyong & Jiang, J.C. & Xiang, Leijun, 2017. "Group-based strategy diffusion in multiplex networks with weighted values," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 148-156.
    11. 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.
    12. Kroumi, Dhaker & Lessard, Sabin, 2015. "Evolution of cooperation in a multidimensional phenotype space," Theoretical Population Biology, Elsevier, vol. 102(C), pages 60-75.
    13. Matthijs van Veelen & Benjamin Allen & Moshe Hoffman & Burton Simon & Carl Veller, 2016. "Inclusive Fitness," Tinbergen Institute Discussion Papers 16-055/I, Tinbergen Institute.
    14. Xinrong Yang & Zhenping Geng & Haitao Li, 2023. "Matrix-Based Method for the Analysis and Control of Networked Evolutionary Games: A Survey," Games, MDPI, vol. 14(2), pages 1-13, February.
    15. Chen, Wei & Wu, Te & Li, Zhiwu & Wang, Long, 2016. "Friendship-based partner switching promotes cooperation in heterogeneous populations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 192-199.
    16. Wang, Chaoqian & Szolnoki, Attila, 2022. "Involution game with spatio-temporal heterogeneity of social resources," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    17. Kyle Weishaar & Igor V. Erovenko, 2022. "The Evolution of Cooperation in Two-Dimensional Mobile Populations with Random and Strategic Dispersal," Games, MDPI, vol. 13(3), pages 1-16, May.
    18. Boyu Zhang & Cong Li & Yi Tao, 2016. "Evolutionary Stability and the Evolution of Cooperation on Heterogeneous Graphs," Dynamic Games and Applications, Springer, vol. 6(4), pages 567-579, December.
    19. Guan, Kaixuan & Chen, Yuyou & Zheng, Wanjun & Zeng, Lulu & Ye, Hang, 2022. "Costly signals can facilitate cooperation and punishment in the prisoner’s dilemma," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    20. Yang, Zhihu & Li, Zhi & Wang, Long, 2020. "Evolution of cooperation in a conformity-driven evolving dynamic social network," Applied Mathematics and Computation, Elsevier, vol. 379(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:phsmap:v:467:y:2017:i:c:p:499-507. 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: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.