Active learning with a misspecified prior
研究了贝叶斯代理人在先验设定错误（即对真实世界状态赋予零概率）下的学习与信息获取行为，刻画了当主观状态空间为双元素时渐近行动与信念的完整特征，并发现短视与耐心代理人的信念收敛性不同。
We study learning and information acquisition by a Bayesian agent whose prior belief is misspecified in the sense that it assigns probability 0 to the true state of the world. At each instant, the agent takes an action and observes the corresponding payoff, which is the sum of a fixed but unknown function of the action and an additive error term. We provide a complete characterization of asymptotic actions and beliefs when the agent's subjective state space is a doubleton. A simple example with three actions shows that in a misspecified environment a myopic agent's beliefs converge while a sufficiently patient agent's beliefs do not. This illustrates a novel interaction between misspecification and the agent's subjective discount rate.