ArticleProceedings of the National Academy of Sciences of the United States of America2022
Evaluating the structure-coefficient theorem of evolutionary game theory.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Hyperedge approximation for stochastic processes on higher-order networks.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Promoting collective cooperation through temporal interactions.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Evolutionary dynamics of any multiplayer game on regular graphs.Nature communications · 2024Article
- Symmetry in models of natural selection.Journal of the Royal Society, Interface · 2023Article
- Evaluating the structure-coefficient theorem of evolutionary game theory.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
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2 authors.
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Abstract
In order to accommodate the empirical fact that population structures are rarely simple, modern studies of evolutionary dynamics allow for complicated and highly heterogeneous spatial structures. As a result, one of the most difficult obstacles lies in making analytical deductions, either qualitative or quantitative, about the long-term outcomes of evolution. The "structure-coefficient" theorem is a well-known approach to this problem for mutation-selection processes under weak selection, but a general method of evaluating the terms it comprises is lacking. Here, we provide such a method for populations of fixed (but arbitrary) size and structure, using easily interpretable demographic measures. This method encompasses a large family of evolutionary update mechanisms and extends the theorem to allow for asymmetric contests to provide a better understanding of the mutation-selection balance under more realistic circumstances. We apply the method to study social goods produced and distributed among individuals in spatially heterogeneous populations, where asymmetric interactions emerge naturally and the outcome of selection varies dramatically, depending on the nature of the social good, the spatial topology, and the frequency with which mutations arise.
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