Evolution of direct reciprocity in group-structured populations.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
04 11 2022
Historique:
received: 28 07 2022
accepted: 01 11 2022
pubmed: 6 11 2022
medline: 9 11 2022
entrez: 5 11 2022
Statut: epublish

Résumé

People tend to have their social interactions with members of their own community. Such group-structured interactions can have a profound impact on the behaviors that evolve. Group structure affects the way people cooperate, and how they reciprocate each other's cooperative actions. Past work has shown that population structure and reciprocity can both promote the evolution of cooperation. Yet the impact of these mechanisms has been typically studied in isolation. In this work, we study how the two mechanisms interact. Using a game-theoretic model, we explore how people engage in reciprocal cooperation in group-structured populations, compared to well-mixed populations of equal size. In this model, the population is subdivided into groups. Individuals engage in pairwise interactions within groups while they also have chances to imitate strategies outside the groups. To derive analytical results, we focus on two scenarios. In the first scenario, we assume a complete separation of time scales. Mutations are rare compared to between-group comparisons, which themselves are rare compared to within-group comparisons. In the second scenario, there is a partial separation of time scales, where mutations and between-group comparisons occur at a comparable rate. In both scenarios, we find that the effect of population structure depends on the benefit of cooperation. When this benefit is small, group-structured populations are more cooperative. But when the benefit is large, well-mixed populations result in more cooperation. Overall, our results reveal how group structure can sometimes enhance and sometimes suppress the evolution of cooperation.

Identifiants

pubmed: 36333592
doi: 10.1038/s41598-022-23467-4
pii: 10.1038/s41598-022-23467-4
pmc: PMC9636277
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

18645

Subventions

Organisme : Japan Society for the Promotion of Science
ID : 21K03362
Organisme : H2020 European Research Council
ID : 850529: E-DIRECT
Organisme : National Research Foundation of Korea
ID : NRF-2020R1I1A2071670

Informations de copyright

© 2022. The Author(s).

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Auteurs

Yohsuke Murase (Y)

RIKEN Center for Computational Science, Kobe, Hyogo, 650-0047, Japan. yohsuke.murase@gmail.com.
Max Planck Research Group 'Dynamics of Social Behavior', Max Planck Institute for Evolutionary Biology, Plön, Germany. yohsuke.murase@gmail.com.

Christian Hilbe (C)

Max Planck Research Group 'Dynamics of Social Behavior', Max Planck Institute for Evolutionary Biology, Plön, Germany.

Seung Ki Baek (SK)

Department of Scientific Computing, Pukyong National University, Busan, 48513, Korea.

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