IDEAS home Printed from https://ideas.repec.org/a/nat/nathum/v3y2019i6d10.1038_s41562-019-0571-0.html
   My bibliography  Save this article

A potential game approach to modelling evolution in a connected society

Author

Listed:
  • Jiabin Wu

    (University of Oregon)

  • Dai Zusai

    (Temple University)

Abstract

When studying human behaviour, it is important to understand not just how individuals interact, but also interactions at the level of communities and populations. Most previous modelling of networks has focused on interactions between individual agents. Here we provide a modelling framework to study the evolution of behaviour in connected populations, by regarding subpopulations as the basic unit of interaction and focusing on the population-level connection structure. We find that when the underlying game played by individuals is a potential game, utilizing such a structure greatly simplifies analysis. In addition, according to known general results on the convergence of evolution dynamics to Nash equilibria in a potential game, our formulation provides a tractable model on behavioural dynamics in social networks that needs only conventional techniques from evolutionary game theory.

Suggested Citation

  • Jiabin Wu & Dai Zusai, 2019. "A potential game approach to modelling evolution in a connected society," Nature Human Behaviour, Nature, vol. 3(6), pages 604-610, June.
    • Handle: RePEc:nat:nathum:v:3:y:2019:i:6:d:10.1038_s41562-019-0571-0
    DOI: 10.1038/s41562-019-0571-0
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41562-019-0571-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1038/s41562-019-0571-0?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hao, Xinyu & Liu, Guangfu & Zhang, Xiaoling & Dong, Liang, 2022. "The coevolution mechanism of stakeholder strategies in the recycled resources industry innovation ecosystem: the view of evolutionary game theory," Technological Forecasting and Social Change, Elsevier, vol. 179(C).

    More about this item

    Statistics

    Access and download statistics

    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:nat:nathum:v:3:y:2019:i:6:d:10.1038_s41562-019-0571-0. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.nature.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.