Epstein, Larry G.Ji, Shaolin2020-04-172020-04-172020-03-16Larry G Epstein, Shaolin Ji. "Optimal learning under robustness and time-consistency." Operations Research, https://doi.org/10.1287/opre.2019.18990030-364Xhttps://hdl.handle.net/2144/40241We model learning in a continuous-time Brownian setting where there is prior ambiguity. The associated model of preference values robustness and is time-consistent. It is applied to study optimal learning when the choice between actions can be postponed, at a per-unit-time cost, in order to observe a signal that provides information about an unknown parameter. The corresponding optimal stopping problem is solved in closed form, with a focus on two specific settings: Ellsberg’s two-urn thought experiment expanded to allow learning before the choice of bets, and a robust version of the classical problem of sequential testing of two simple hypotheses about the unknown drift of a Wiener process. In both cases, the link between robustness and the demand for learning is studied.en-USOperations researchApplied mathematicsComputation theory and mathematicsBusiness and managementArticle10.1287/opre.2019.1899511909