EconPapers    
Economics at your fingertips  
 

A potential game approach to modelling evolution in a connected society

Jiabin Wu () and Dai Zusai ()
Additional contact information
Dai Zusai: Temple University

Nature Human Behaviour, 2019, vol. 3, issue 6, 604-610

Abstract: 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.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.nature.com/articles/s41562-019-0571-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:nathum:v:3:y:2019:i:6:d:10.1038_s41562-019-0571-0

Ordering information: This journal article can be ordered from
https://www.nature.com/nathumbehav/

DOI: 10.1038/s41562-019-0571-0

Access Statistics for this article

Nature Human Behaviour is currently edited by Stavroula Kousta

More articles in Nature Human Behaviour from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-19
Handle: RePEc:nat:nathum:v:3:y:2019:i:6:d:10.1038_s41562-019-0571-0