Perturbation theory for evolution of cooperation on networks.

Evolutionary game Fixation Network reciprocity Prisoner’s dilemma Stochastic dynamics

Journal

Journal of mathematical biology
ISSN: 1432-1416
Titre abrégé: J Math Biol
Pays: Germany
ID NLM: 7502105

Informations de publication

Date de publication:
19 06 2023
Historique:
received: 06 02 2023
accepted: 20 05 2023
revised: 09 05 2023
medline: 21 6 2023
pubmed: 19 6 2023
entrez: 19 6 2023
Statut: epublish

Résumé

Network structure is a mechanism for promoting cooperation in social dilemma games. In the present study, we explore graph surgery, i.e., to slightly perturb the given network, towards a network that better fosters cooperation. To this end, we develop a perturbation theory to assess the change in the propensity of cooperation when we add or remove a single edge to/from the given network. Our perturbation theory is for a previously proposed random-walk-based theory that provides the threshold benefit-to-cost ratio, [Formula: see text], which is the value of the benefit-to-cost ratio in the donation game above which the cooperator is more likely to fixate than in a control case, for any finite networks. We find that [Formula: see text] decreases when we remove a single edge in a majority of cases and that our perturbation theory captures at a reasonable accuracy which edge removal makes [Formula: see text] small to facilitate cooperation. In contrast, [Formula: see text] tends to increase when we add an edge, and the perturbation theory is not good at predicting the edge addition that changes [Formula: see text] by a large amount. Our perturbation theory significantly reduces the computational complexity for calculating the outcome of graph surgery.

Identifiants

pubmed: 37335377
doi: 10.1007/s00285-023-01941-5
pii: 10.1007/s00285-023-01941-5
pmc: PMC10279588
doi:

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

12

Informations de copyright

© 2023. The Author(s).

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Auteurs

Lingqi Meng (L)

Department of Mathematics, University at Buffalo, State University of New York, Buffalo, NY, 14260-2900, USA.

Naoki Masuda (N)

Department of Mathematics, University at Buffalo, State University of New York, Buffalo, NY, 14260-2900, USA. naokimas@gmail.com.
Computational and Data-Enabled Science and Engineering Program, University at Buffalo, State University of New York, Buffalo, NY, 14260-5030, USA. naokimas@gmail.com.

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Classifications MeSH