A Partial Folk Theorem for Games with Unknown Payoff Distributions
研究收益分布未知的重复博弈，证明在完美监测和足够耐心下，存在序贯均衡使玩家通过实验学习状态并接近各状态下的可行个体理性收益。
Repeated games with unknown payoff distributions are analogous to a single decision maker's "multi-armed bandit" problem. Each state of the world corresponds to a different payoff matrix of a stage game. When monitoring is perfect, information about the state is public, and players are sufficiently patient, the following result holds: For any function that maps each state to a payoff vector that is feasible and individually rational in that state, there is a sequential equilibrium in which players experiment to learn the realized state and achieve a payoff close to the one specified for that state. Copyright The Econometric Society 2005.