标题： 最大后验学习在需求竞争博弈中 显示英文标题

标题： Maximum a posteriori learning in demand competition games

摘要： 我们考虑两个企业之间的库存竞争博弈。 我们解决的问题是：如果参与者不知道对手的行动，且对手的效用函数未知，他们是否可以通过观察自己的销售在重复博弈中学会纳什策略？ 在本工作中证明，通过最大后验（MAP）估计，参与者可以学习纳什策略。 证明了参与者的行动和信念会收敛到纳什均衡。 显示英文摘要

摘要： We consider an inventory competition game between two firms. The question we address is this: If players do not know the opponent's action and opponent's utility function can they learn to play the Nash policy in a repeated game by observing their own sales? In this work it is proven that by means of Maximum A Posteriori (MAP) estimation, players can learn the Nash policy. It is proven that players' actions and beliefs do converge to the Nash equilibrium.