作者：Cheng, Xiaoyu
作者单位：State University System of Florida; Florida State University
摘要：A decision-maker faces uncertainty governed by a data-generating process (DGP), which is only known to belong to a set of sequences of independent but possibly non-identical distributions. A robust decision maximizes the expected payoff against the worst possible DGP in this set. This paper characterizes when and how such robust decisions can be objectively improved with data; that is, can yield higher expected payoffs under the true DGP regardless of which DGP is the truth. It further develop...
