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Although cooperation and trust are essential features for the development of prosperous populations, they also put cooperating individuals at risk for exploitation and abuse. Empirical and theoretical evidence suggests that the solution to the problem resides in the practice of mimicry and imitation, the expectation of opponent's mimicry and the reliance on similarity indices. Here we fuse the principles of enacted and expected mimicry and condition their application on two similarity indices to produce a model of mimicry and relative similarity. Testing the model in computer simulations of behavioral niches, populated with agents that enact various strategies and learning algorithms, shows how mimicry and relative similarity outperforms all the opponent strategies it was tested against, pushes noncooperative opponents toward extinction, and promotes the development of cooperative populations. The proposed model sheds light on the evolution of cooperation and provides a blueprint for intentional induction of cooperation within and among populations. It is suggested that reducing conflict intensities among human populations necessitates (i) instigation of social initiatives that increase the perception of similarity among opponents and (ii) efficient lowering of the similarity threshold of the interaction, the minimal level of similarity that makes cooperation advisable.

Fusing enacted and expected mimicry generates a winning strategy that promotes the evolution of cooperation