Frequency-dependent returns in nonlinear public goods games.

evolutionary game theory finite and infinite populations public goods games social dilemmas

Journal

Journal of the Royal Society, Interface
ISSN: 1742-5662
Titre abrégé: J R Soc Interface
Pays: England
ID NLM: 101217269

Informations de publication

Date de publication:
Oct 2024
Historique:
medline: 30 10 2024
pubmed: 30 10 2024
entrez: 29 10 2024
Statut: ppublish

Résumé

When individuals interact in groups, the evolution of cooperation is traditionally modelled using the framework of public goods games. These models often assume that the return of the public goods depends linearly on the fraction of contributors. In contrast, in real-life public goods interactions, the return can depend on the size of the investor pool as well. Here, we consider a model in which the multiplication factor (marginal per capita return) for the public goods depends linearly on how many contribute, which results in a nonlinear model of public goods. This simple model breaks the curse of dominant defection found in linear public goods interactions and gives rise to richer dynamical outcomes in evolutionary settings. We provide an in-depth analysis of the more varied decisions by the classical rational player in nonlinear public goods interactions as well as a mechanistic, microscopic derivation of the evolutionary outcomes for the stochastic dynamics in finite populations and in the deterministic limit of infinite populations. This kind of nonlinearity provides a natural way to model public goods with diminishing returns as well as economies of scale.

Identifiants

pubmed: 39471869
doi: 10.1098/rsif.2024.0334
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

20240334

Subventions

Organisme : Natural Sciences and Engineering Research Council of Canada

Auteurs

Christoph Hauert (C)

Department of Mathematics, University of British Columbia, Vancouver B.C. V6T 1Z2, Canada.
Department of Zoology, University of British Columbia, Vancouver B.C. V6T 1Z4, Canada.

Alex McAvoy (A)

School of Data Science and Society, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Department of Mathematics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.

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