A note on the strong formulation of stochastic control problems with model uncertainty

Abstract

We consider a Markovian stochastic control problem with model uncertainty. The controller (intelligent player) observes only the state, and, therefore, uses feed-back (closed-loop) strategies. The adverse player (nature) who does not have a direct interest in the pay-off, chooses open-loop controls that parametrize Knightian uncertainty. This creates a two-step optimization problem (like half of a game) over feed-back strategies and open-loop controls. The main result is to show that, under some assumptions, this provides the same value as the (half of) the zero-sum symmetric game where the adverse player also plays feed-back strategies and actively tries to minimize the pay-off. The value function is independent of the filtration accessible to the adverse player. Aside from the modeling issue, the present note is a technical companion to [S\^I3b].