Trust Region Constrained Measure Transport in Path Space for Stochastic Optimal Control and Inference

Understand

Solving stochastic optimal control problems with quadratic control costs can be viewed as approximating a target path space measure, e.g.

• via gradient-based optimization.
• In practice, however, this optimization is challenging in particular if the target measure differs substantially from the prior.
• In this work, we therefore approach the problem by iteratively solving constrained problems incorporating trust regions that aim for approaching the target measure gradually in a systematic way.