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We study aggregate behaviour in a setting where individuals repeatedly interact via a network to play a minimum-effort (stag hunt) game. Of interest is whether play converges on the Pareto-optimal or risk-dominant outcome. We contrast the best-reply dynamic with the imitate-the-best dynamic. We also contrast forms of lattice, small-world and random networks. Our main finding is that play is far more likely to converge on the Pareto-optimal outcome if individuals learn by imitation. We find that play in small-world networks is similar to that in a regular network.
