IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v612y2023ics0378437123000390.html
   My bibliography  Save this article

The emergence of a core–periphery structure in evolving multilayer network

Author

Listed:
  • Beranek, L.
  • Remes, R.

Abstract

The application of the evolutionary game method to studying dynamics on multilayer networks is a current hot issue. However, most current evolutionary game models do not consider some constraints affecting the development of the relationship structure in a multilayer network. Therefore, this paper proposes a new model to explain the emergence and evolution of core and periphery structures in a multilayer network. Our model includes the direct costs of maintaining interactions between players in the game model. We also introduce the ability to end disadvantageous interactions (a defective neighbor that does not bring benefits is disconnected). Third, when establishing new relationships, a player establishes a relationship with another based on the estimate (trust) that this player will cooperate. The simulation results show that a core of densely connected cooperative players gradually emerges, isolating defectors on the periphery and gaining additional advantages. The proposed model contributes to understanding the emergence and development of the core–periphery structure in a multilayered network with a core formed either between players in the same layers or between players from other layers (across layers).

Suggested Citation

  • Beranek, L. & Remes, R., 2023. "The emergence of a core–periphery structure in evolving multilayer network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 612(C).
  • Handle: RePEc:eee:phsmap:v:612:y:2023:i:c:s0378437123000390
    DOI: 10.1016/j.physa.2023.128484
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437123000390
    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.2023.128484?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. 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.
    2. Francisco C Santos & Jorge M Pacheco & Tom Lenaerts, 2006. "Cooperation Prevails When Individuals Adjust Their Social Ties," PLOS Computational Biology, Public Library of Science, vol. 2(10), pages 1-8, October.
    3. Theodore C. Bergstrom, 2002. "Evolution of Social Behavior: Individual and Group Selection," Journal of Economic Perspectives, American Economic Association, vol. 16(2), pages 67-88, Spring.
    4. Nobuyuki Hanaki & Alexander Peterhansl & Peter S. Dodds & Duncan J. Watts, 2007. "Cooperation in Evolving Social Networks," Management Science, INFORMS, vol. 53(7), pages 1036-1050, July.
    5. Li, Gang & Sun, Xiaochen, 2021. "Evolutionary game on a growing multilayer network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).
    6. Vinícius da Fonseca Vieira & Carolina Ribeiro Xavier & Nelson Francisco Favilla Ebecken & Alexandre Gonçalves Evsukoff, 2014. "Performance Evaluation of Modularity Based Community Detection Algorithms in Large Scale Networks," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-15, December.
    7. Wu, Jiadong & Zhao, Chengye, 2020. "Better immigration: Prisoner’s dilemma game with population change on dynamic network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    8. Qi Su & Alex McAvoy & Yoichiro Mori & Joshua B. Plotkin, 2022. "Evolution of prosocial behaviours in multilayer populations," Nature Human Behaviour, Nature, vol. 6(3), pages 338-348, March.
    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. Wang, Chaoqian & Sun, Chengbin, 2023. "Public goods game across multilayer populations with different densities," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    2. Jason Barr & Troy Tassier, 2010. "Endogenous Neighborhood Selection and the Attainment of Cooperation in a Spatial Prisoner’s Dilemma Game," Computational Economics, Springer;Society for Computational Economics, vol. 35(3), pages 211-234, March.
    3. Du, Jinming & Wu, Ziren, 2022. "Evolutionary dynamics of cooperation in dynamic networked systems with active striving mechanism," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    4. Du, Jinming & Wu, Ziren, 2023. "Coevolutionary dynamics of strategy and network structure with publicity mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 623(C).
    5. Jorge M Pacheco & Flávio L Pinheiro & Francisco C Santos, 2009. "Population Structure Induces a Symmetry Breaking Favoring the Emergence of Cooperation," PLOS Computational Biology, Public Library of Science, vol. 5(12), pages 1-7, December.
    6. Faqi Du & Feng Fu, 2011. "Partner Selection Shapes the Strategic and Topological Evolution of Cooperation," Dynamic Games and Applications, Springer, vol. 1(3), pages 354-369, September.
    7. Tanimoto, Jun, 2009. "Promotion of cooperation through co-evolution of networks and strategy in a 2 × 2 game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(6), pages 953-960.
    8. van den Bergh, Jeroen C.J.M. & Gowdy, John M., 2009. "A group selection perspective on economic behavior, institutions and organizations," Journal of Economic Behavior & Organization, Elsevier, vol. 72(1), pages 1-20, October.
    9. Hirofumi Takesue, 2020. "From defection to ingroup favoritism to cooperation: simulation analysis of the social dilemma in dynamic networks," Journal of Computational Social Science, Springer, vol. 3(1), pages 189-207, April.
    10. Matthias Greiff, 2013. "Rewards and the private provision of public goods on dynamic networks," Journal of Evolutionary Economics, Springer, vol. 23(5), pages 1001-1021, November.
    11. 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.
    12. Julia Poncela & Jesús Gómez-Gardeñes & Luis M Floría & Angel Sánchez & Yamir Moreno, 2008. "Complex Cooperative Networks from Evolutionary Preferential Attachment," PLOS ONE, Public Library of Science, vol. 3(6), pages 1-6, June.
    13. Rossana Mastrandrea & Leonardo Boncinelli & Ennio Bilancini, 2023. "Coevolution of cognition and cooperation in structured populations under reinforcement learning," Papers 2306.11376, arXiv.org, revised Mar 2024.
    14. Bin Wu & Da Zhou & Feng Fu & Qingjun Luo & Long Wang & Arne Traulsen, 2010. "Evolution of Cooperation on Stochastic Dynamical Networks," PLOS ONE, Public Library of Science, vol. 5(6), pages 1-7, June.
    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. Luthi, Leslie & Pestelacci, Enea & Tomassini, Marco, 2008. "Cooperation and community structure in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 955-966.
    17. 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).
    18. Daniel Ladley & Ian Wilkinson & Louise Young, 2013. "The Evolution Of Cooperation In Business: Individual Vs. Group Incentives," Discussion Papers in Economics 13/14, Division of Economics, School of Business, University of Leicester.
    19. Guo, Yujie & Zhang, Liming & Li, Haihong & Dai, Qionglin & Yang, Junzhong, 2023. "Network adaption based on environment feedback promotes cooperation in co-evolutionary games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 617(C).
    20. Michael Foley & Rory Smead & Patrick Forber & Christoph Riedl, 2021. "Avoiding the bullies: The resilience of cooperation among unequals," PLOS Computational Biology, Public Library of Science, vol. 17(4), pages 1-18, April.

    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:612:y:2023:i:c:s0378437123000390. 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.