文章基本信息

标题：Active learning with a misspecified prior
本地全文：下载
作者：Drew Fudenberg ; Drew Fudenberg ; Gleb Romanyuk 等
期刊名称：Theoretical Economics
印刷版ISSN：1555-7561
出版年度：2017
卷号：12
期号：3
页码：1155-1189
DOI：10.3982/TE2480
语种：English
出版社：Econometric Society
摘要：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.
关键词：Active learning learning in games misspecified models D83 D90