Full Cooperation in Repeated Multi-Player Games on Hypergraphs

Abstract: Nearly all living systems, especially humans, depend on collective cooperation for survival and prosperity. However, the mechanisms driving the evolution of cooperative behavior remain poorly understood, particularly in the context of simultaneous interactions involving multiple individuals, repeated encounters, and complex interaction structures. Here, we introduce a novel framework for studying repeated multi-player interactions in structured populations -- repeated multi-player games on hypergraphs -- where multiple individuals within each hyperedge engage in a repeated game, and each player can simultaneously participate in many games. We focus on public goods games, where individuals differ in their initial endowments, their allocation of endowments across games, and their productivity, which determines the impact of their contributions. Through Nash equilibrium analysis, we reveal the intricate interplay between full cooperation (all individuals contribute their entire endowments, maximizing collective benefits) and key factors such as initial endowments, productivity, contribution strategies, and interaction structure. Notably, while equal endowments are most effective in promoting full cooperation in homogeneous hypergraphs, they can hinder cooperation in heterogeneous hypergraphs, suggesting that equal endowments are not universally optimal. To address this, we propose two optimization strategies: one for policymakers to adjust endowment distributions and another for players to modify their contribution strategies. Both approaches successfully promote full cooperation across all studied hypergraphs. Our findings provide novel insights into the emergence of full cooperation, offering valuable guidance for both players and policymakers in fostering collective cooperation.