Evolution of cooperation in multichannel games on multiplex networks

Humans navigate diverse social relationships and concurrently interact across multiple social contexts. An individual's behavior in one context can influence behavior in other contexts. Different payoffs associated with interactions in the different domains have motivated recent studies of the evolution of cooperation through the analysis of multichannel games where each individual is simultaneously engaged in multiple repeated games. However, previous investigations have ignored the potential role of network structure in each domain and the effect of playing against distinct interacting partners in different domains. Multiplex networks provide a useful framework to represent social interactions between the same set of agents across different social contexts. We investigate the role of multiplex network structure and strategy linking in multichannel games on the spread of cooperative behavior in all layers of the multiplex. We find that multiplex structure along with strategy linking enhances the cooperation rate in all layers of the multiplex compared to a well-mixed population in Prisoners' Dilemma games, provided the network structure is identical across layers. The effectiveness of strategy linking in enhancing cooperation depends on the degree of similarity of the network structure across the layers and perception errors due to imperfect memory. Higher cooperation rates are achieved when the degree of structural overlap of the different layers is sufficiently large, and the probability of perception error is relatively low. Our work reveals how the social network structure in different layers of a multiplex can affect the spread of cooperation by limiting the ability of individuals to link strategies across different social domains.

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Publication Details

Journal
PLoS Computational Biology
Published
2024-12-19
DOI
https://doi.org/10.1371/journal.pcbi.1012678
Citations
7
Primary Topic
Evolutionary Game Theory and Cooperation
Type
article
Field-Weighted Citation Impact
7.92

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article

Evolution of cooperation in multichannel games on multiplex networks

Supratim Sengupta, Amit Basak
7 citations
PLoS Computational Biology
Evolutionary Game Theory and Cooperation
7.92
article

Evolution of cooperation in multichannel games on multiplex networks

Supratim Sengupta, Amit Basak
article en
7 citations

Abstract

Humans navigate diverse social relationships and concurrently interact across multiple social contexts. An individual's behavior in one context can influence behavior in other contexts. Different payoffs associated with interactions in the different domains have motivated recent studies of the evolution of cooperation through the analysis of multichannel games where each individual is simultaneously engaged in multiple repeated games. However, previous investigations have ignored the potential role of network structure in each domain and the effect of playing against distinct interacting partners in different domains. Multiplex networks provide a useful framework to represent social interactions between the same set of agents across different social contexts. We investigate the role of multiplex network structure and strategy linking in multichannel games on the spread of cooperative behavior in all layers of the multiplex. We find that multiplex structure along with strategy linking enhances the cooperation rate in all layers of the multiplex compared to a well-mixed population in Prisoners' Dilemma games, provided the network structure is identical across layers. The effectiveness of strategy linking in enhancing cooperation depends on the degree of similarity of the network structure across the layers and perception errors due to imperfect memory. Higher cooperation rates are achieved when the degree of structural overlap of the different layers is sufficiently large, and the probability of perception error is relatively low. Our work reveals how the social network structure in different layers of a multiplex can affect the spread of cooperation by limiting the ability of individuals to link strategies across different social domains.

PLoS Computational BiologyVol. 20(12)
Indian Institute of Science Education and Research Kolkata (IN)
Indian Institute of Science Education and Research Mohali, Indian Institute of Science Education and Research Kolkata, Science and Engineering Research Board
Partnerships for the goals
Openalex Percentile: Top 3%
Evolutionary Game Theory and Cooperation
7.92
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Evolution of cooperation in multichannel games on multiplex networks — Supratim Sengupta, Amit Basak · PLoS Computational Biology (2024) | TGRS Research Map | TGRS