Individual Learning and Cooperation in Noisy Repeated Games
研究了在博弈细节未知的长期关系中，两个玩家如何通过个体学习维持合作，发现存在稳健均衡使玩家最终获得如同真实状态为共同知识时的收益。
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 learned. We show that there are robust equilibria in which players eventually obtain payoffs as if the true state were common knowledge and players played a "belief-free" equilibrium. We also provide explicit equilibrium constructions in various economic examples. Copyright 2014, Oxford University Press.