Prolonged Learning and Hasty Stopping: The Wald Problem with Ambiguity
研究模糊厌恶决策者在采取不可逆行动前如何决定信息收集时长，发现与贝叶斯决策者相比，其在适度不确定性下过度实验，在高不确定性下可能提前停止，且停止规则非单调并包含随机停止。
This paper studies sequential information acquisition by an ambiguity-averse decision-maker (DM), who decides how long to collect information before taking an irreversible action. The agent optimizes against the worst-case belief and updates prior by prior. We show that the consideration of ambiguity gives rise to rich dynamics: compared to the Bayesian DM, the DM here tends to experiment excessively when facing modest uncertainty and, to counteract it, may stop experimenting prematurely when facing high uncertainty. In the latter case, the DM’s stopping rule is nonmonotonic in beliefs and features randomized stopping.