Inefficient Learning Leads to Efficient Coordination: A Repeated Stag-Hunt Game with Learning Agents

In coordination games, the distinctive presence of multiple equilibria poses a challenge to coordination, and this has led over time to the proposal of numerous determinants of the latter. In this paper, we study coordination in a repeated Stag-hunt game played by two agents who are able to learn from the outcomes of each game, but do not know the payoff matrix. By modulating their learning capabilities, we show that agents are able to coordinate on the social optimum when they learn slowly from experience and are prone to making mistakes. A comparison with the results from a recent laboratory experiment is also provided.