ArticlePLoS computational biology2014
Evolutionary game dynamics in populations with heterogenous structures.
Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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Who cites it
38 citing papers in PubMed.
- Public goods games on any population structure.Science advances · 2026Article
- Promoters of cooperation in evolutionary games.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Emergence of cooperation promoted by higher-order strategy updates.PLoS computational biology · 2025Article
- Emergence of a complex network structure on a Spatial Prisoner's Dilemma.PLoS computational biology · 2025Article
- Using spatial statistics to infer game-theoretic interactions in an agent-based model of cancer cells.bioRxiv : the preprint server for biology · 2025Article
- Behavioural strategies in simultaneous and alternating prisoner's dilemma games with/without voluntary participation.Scientific reports · 2024Article
- Evolutionary graph theory beyond single mutation dynamics: on how network-structured populations cross fitness landscapes.Genetics · 2024Article
- Dynamics of collective cooperation under personalised strategy updates.Nature communications · 2024Article
- Network topology and movement cost, not updating mechanism, determine the evolution of cooperation in mobile structured populations.PloS one · 2023Article
- Data-driven evolutionary game models for the spread of fairness and cooperation in heterogeneous networks.Frontiers in psychiatry · 2023Article
- The role of evolutionary game theory in spatial and non-spatial models of the survival of cooperation in cancer: a review.Journal of the Royal Society, Interface · 2022Review
- Oxytocin and the Punitive Hub-Dynamic Spread of Cooperation in Human Social Networks.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022Article
- Evaluating the structure-coefficient theorem of evolutionary game theory.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Evolution of prosocial behaviours in multilayer populations.Nature human behaviour · 2022Article
- Fixation probabilities in evolutionary dynamics under weak selection.Journal of mathematical biology · 2021Article
- Social goods dilemmas in heterogeneous societies.Nature human behaviour · 2020Article
- Environmental spatial and temporal variability and its role in non-favoured mutant dynamics.Journal of the Royal Society, Interface · 2019Article
- Computation and Simulation of Evolutionary Game Dynamics in Finite Populations.Scientific reports · 2019Article
- Evolution of cooperation in an epithelium.Journal of the Royal Society, Interface · 2019Article
- Parent-preferred dispersal promotes cooperation in structured populations.Proceedings. Biological sciences · 2019Article
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Evolutionary graph theory is a well established framework for modelling the evolution of social behaviours in structured populations. An emerging consensus in this field is that graphs that exhibit heterogeneity in the number of connections between individuals are more conducive to the spread of cooperative behaviours. In this article we show that such a conclusion largely depends on the individual-level interactions that take place. In particular, averaging payoffs garnered through game interactions rather than accumulating the payoffs can altogether remove the cooperative advantage of heterogeneous graphs while such a difference does not affect the outcome on homogeneous structures. In addition, the rate at which game interactions occur can alter the evolutionary outcome. Less interactions allow heterogeneous graphs to support more cooperation than homogeneous graphs, while higher rates of interactions make homogeneous and heterogeneous graphs virtually indistinguishable in their ability to support cooperation. Most importantly, we show that common measures of evolutionary advantage used in homogeneous populations, such as a comparison of the fixation probability of a rare mutant to that of the resident type, are no longer valid in heterogeneous populations. Heterogeneity causes a bias in where mutations occur in the population which affects the mutant's fixation probability. We derive the appropriate measures for heterogeneous populations that account for this bias.
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