A POLICY GRADIENT FRAMEWORK FOR STOCHASTIC OPTIMAL CONTROL PROBLEMS WITH GLOBAL CONVERGENCE GUARANTEE

We consider policy gradient methods for stochastic optimal control problems in continuous time. In particular, we analyze the gradient flow for the control, viewed as a continuous time limit of the policy gradient method. We prove the global convergence of the gradient flow and establish a convergence rate under some regularity assumptions. The main novelty in the analysis is the notion of local optimal control function, which is introduced to characterize the local optimality of the iterate.

Duke Scholars

Author Jianfeng Lu Mathematics