arXiv · 2609.33556
When groups attract: coevolutionary dynamics of cooperation and individual- and group-based imitating rules
Abstract
Success-driven imitation is a fundamental aspect of social learning, yet group interactions beyond pairwise require more subtle imitating rules since success can be observed at either the group or individual level. How such heuristic imitating rules based on these distinct levels of social information compete and coevolve with collective behavior, particularly cooperation, remains poorly understood. Here, we address this issue by studying the coevolutionary dynamics of cooperation in public goods games and individual- and group-based imitating rules on hypergraphs. We distinguish three rules according to whether payoff-biased imitation operates at the individual level, the group level, or both. Our results identify a mutual reinforcement between cooperation and group-biased imitation: preferentially learning from successful groups promotes cooperation, while cooperators in turn favor group-biased imitation. We confirm this synergy between cooperation and group-biased imitation across diverse synthetic and empirical higher-order network populations. We further show that the subtle scale and organization of group interactions critically shape this coevolution, with intermediate group sizes providing the greatest advantage for cooperation. Our results reveal how learning whom to imitate can jointly evolve to shape collective cooperation.
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Dini Wang, Peng Yi, Gang Yan, Feng Fu. 2026-09-27. When groups attract: coevolutionary dynamics of cooperation and individual- and group-based imitating rules. https://arxiv.org/abs/2609.33556
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