Imitation dynamics on networks with incomplete social information

Abstract

Imitation is an important social learning heuristic in animal and human societies that drives the evolution of collective behaviors. Previous explorations find that the fate of cooperators has a sensitive dependence on the protocol of imitation, including the number of social peers used for comparison and whether one's own performance is considered. This leads to a puzzle about how to quantify the impact of different styles of imitation on the evolution of cooperation. Here, we take a novel perspective on the personal and social information required by imitation. We develop a general model of imitation dynamics with incomplete social information, which unifies classical imitation processes including death-birth and pairwise-comparison update rules. In pairwise social dilemmas, we find that cooperation is most easily promoted if individuals neglect personal information when imitating. If personal information is considered, cooperators evolve more readily with more social information. Intriguingly, when interactions take place in larger groups on networks with low degrees of clustering, using more personal and less social information better facilitates cooperation. We offer a unifying perspective uncovering intuition behind these phenomena by examining the rate and range of competition induced by different social dilemmas.Comment: 14pages, 5 figure