Metric clusters in evolutionary games on scale-free networks

Abstract

The evolution of cooperation in social dilemmas in structured populations has been studied extensively in recent years. Whereas many theoretical studies have found that a heterogeneous network of contacts favors cooperation, the impact of spatial effects in scale-free networks is still not well understood. In addition to being heterogeneous, real contact networks exhibit a high mean local clustering coefficient, which implies the existence of an underlying metric space. Here, we show that evolutionary dynamics in scale-free networks self-organize into spatial patterns in the underlying metric space. The resulting metric clusters of cooperators are able to survive in social dilemmas as their spatial organization shields them from surrounding defectors, similar to spatial selection in Euclidean space. We show that under certain conditions these metric clusters are more efficient than the most connected nodes at sustaining cooperation and that heterogeneity does not always favor--but can even hinder--cooperation in social dilemmas. Our findings provide a new perspective to understand the emergence of cooperation in evolutionary games in realistic structured populations.

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Cited by in corpus (8)

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• Emergence of geometric Turing patterns in complex networks
• Topological enslavement in evolutionary games on correlated multiplex networks
• The evolution of cooperation in spatial public goods game with tolerant punishment based on reputation threshold
• Importance of initial conditions in the polarization of complex networks
• Geometric detection of hierarchical backbones in real networks
• Random walk with hyperbolic probabilities
• The cooperation-defection evolution on social networks