ArticleJournal of mathematical biology2023
Perturbation theory for evolution of cooperation on networks.
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.
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2 authors.
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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.
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