Strategy evolution on higher-order networks

Anzhi Sheng

doi:10.1038/s43588-024-00621-8

Strategy evolution on higher-order networks

2024-04-15

15

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AI

DOI：10.1038/s43588-024-00621-8

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Abstract

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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. Cooperation is not merely a dyadic phenomenon, it also includes multi-way social interactions. A mathematical framework is developed to study how the structure of higher-order interactions influences cooperative behavior.

Keywords:

GROUP-SIZE

COOPERATION

DYNAMICS

EMERGENCE

SELECTION

GAMES

DIVERSITY

GRAPHS

Strategy evolution on higher-order networks

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