Thomas Lew (Toyota Research Institute) – New Optimality Conditions and an Indirect Shooting Method for Stochastic Optimal Control

Abstract: Efficiently solving nonlinear stochastic optimal control problems remains a challenge with many applications. Existing optimality conditions typically rely on forward-backward stochastic differential equations (FBSDEs), which can be difficult to use in algorithms. In this talk, I will present new optimality conditions for stochastic optimal control, derived using rough path theory. This Pontryagin Maximum Principle uses the same Hamiltonian as in the deterministic setting, while avoiding FBSDEs. It unlocks the first indirect shooting method for stochastic optimal control, which only searches over the initial adjoint state and converges significantly faster than a direct method in numerical experiments. I will present applications to driving at the limits of handling and future directions towards robust and efficient uncertainty-aware control.