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Single Time-scale Actor-critic Method to Solve the Linear Quadratic Regulator with Convergence Guarantees by Zhou, Mo; Lu, Jianfeng is a scholarly article available to read on EtoBox.

What is Single Time-scale Actor-critic Method to Solve the Linear Quadratic Regulator with Convergence Guarantees about?

We propose a single time-scale actor-critic algorithm to solve the linear quadratic regulator (LQR) problem. A least squares temporal difference (LSTD) method is applied to the critic and a natural policy gradient method is used for the actor. We give a proof of convergence with sample complexity $\mathcal{O}(\varepsilon^{-1} \log(\varepsilon^{-1})^2)$. The method in the proof is applicable to general single time-scale bilevel optimization problem. We also numerically validate our theoretical results on the convergence.

Author

Zhou, Mo; Lu, Jianfeng

Published

2022

Language

EN