Learning in a Correlated World
综述了相关学习的研究，即当结果相关时，一个选择的信息如何改变对其他选择的信念。该框架应用于搜索与实验、沟通、创新与市场竞争、属性问题四个经典经济问题，并回顾了实证与实验证据。
We survey a growing literature on correlated learning—that is, how information from one choice changes beliefs about others when outcomes are correlated. The core modeling innovation is to represent the unknown mapping from choices to outcomes as the realized path of a stochastic process, most commonly the Brownian motion. We show how the framework has been applied to four canonical economic problems in which correlated learning is key but understudied: ( a ) search and experimentation, ( b ) communication, ( c ) innovation and market competition, and ( d ) attribute problems. We review emerging empirical and experimental evidence on correlated learning and outline new theoretical and methodological directions.