Policy Gradient Methods for Discrete Time Linear Quadratic Regulator With Random Parameters

arXiv:2303.16548v2 Announce Type: replace-cross
Abstract: This paper studies an infinite horizon optimal control problem for discrete-time linear system and quadratic criteria, both with random parameters which are independent and identically distributed with respect to time. In this general setting, we apply the policy gradient method, a reinforcement learning technique, to search for the optimal control without requiring knowledge of statistical information of the parameters. We investigate the sub-Gaussianity of the state process and establish global linear convergence guarantee for this …

abstract apply arxiv control cs.lg distributed general gradient horizon independent linear math.oc paper parameters policy random regulator reinforcement reinforcement learning studies type