Individual Learning and Cooperation in Noisy Repeated Games
We investigate whether two players in a long-run relationship can maintain cooperation when the details of the underlying game are unknown. Specifically, we consider a new class of repeated games with private monitoring, where an unobservable state of the world influences the payoff functions and/or the monitoring structure. Each player privately learns the state over time, but cannot observe what the opponent learns. We show that there are robust equilibria where players eventually obtain payoffs as if the true state were common knowledge and players played a “belief-free” equilibrium. The result is applied to various examples, including secret pricecutting with unknown demand.