1st Monday of each month
Time: 5:00 pm – 6:00 pm
Date: 06th of November 2017
Place: Room 3105
Nicolas BARADEL (CREST) – “Optimal control under uncertainty and bayesian parameters adjustments”
Abstract: We propose a general framework for studying optimal impulse control problem in the presence of uncertainty on the parameters. Given a prior on the distribution of the unknown parameters, we explain how it should evolve according to the classical Bayesian rule after each impulse. Taking these progressive prior-adjustments into account, we characterize the optimal policy through a quasi-variational parabolic equation, which can be solved numerically. The derivation of the dynamic programming equation seems to be new in this context. The main difficulty lies in the nature of the set of controls which depends in a non trivial way on the initial data through the filtration itself.