Strategy evolution on higher-order networks

A Sheng, Q Su, L Wang, JB Plotkin - Nature Computational Science, 2024 - nature.com
Nature Computational Science, 2024nature.com
Cooperation is key to prosperity in human societies. Population structure is well understood
as a catalyst for cooperation, where research has focused on pairwise interactions. But
cooperative behaviors are not simply dyadic, and they often involve coordinated behavior in
larger groups. Here we develop a framework to study the evolution of behavioral strategies
in higher-order population structures, which include pairwise and multi-way interactions. We
provide an analytical treatment of when cooperation will be favored by higher-order …
Abstract
Cooperation is key to prosperity in human societies. Population structure is well understood as a catalyst for cooperation, where research has focused on pairwise interactions. But cooperative behaviors are not simply dyadic, and they often involve coordinated behavior in larger groups. Here we develop a framework to study the evolution of behavioral strategies in higher-order population structures, which include pairwise and multi-way interactions. We provide an analytical treatment of when cooperation will be favored by higher-order interactions, accounting for arbitrary spatial heterogeneity and nonlinear rewards for cooperation in larger groups. Our results indicate that higher-order interactions can act to promote the evolution of cooperation across a broad range of networks, in public goods games. Higher-order interactions consistently provide an advantage for cooperation when interaction hyper-networks feature multiple conjoined communities. Our analysis provides a systematic account of how higher-order interactions modulate the evolution of prosocial traits.
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