Evidence map›Paper›PMID 37335377›Full record

ArticleJournal of mathematical biology2023

Perturbation theory for evolution of cooperation on networks.

Lingqi Meng, Naoki Masuda

Abstract read
In one paragraph

Article in Journal of mathematical biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Lingqi MengDepartment of Mathematics, University at Buffalo, State University of New York, Buffalo, NY, 14260-2900, USA.ORCID http://orcid.org/0000-0001-9986-9205
Naoki MasudaDepartment of Mathematics, University at Buffalo, State University of New York, Buffalo, NY, 14260-2900, USA. naokimas@gmail.com.ORCID http://orcid.org/0000-0003-1567-801X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Cooperative BehaviorGame TheoryBiological EvolutionCost-Benefit AnalysisEvolutionary gameFixationNetwork reciprocityPrisoner’s dilemmaStochastic dynamics

Identifiers

PMID37335377
PMCPMC10279588

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.