Towards a Theoretical Foundation of Policy Optimization for Learning
Control Policies

Towards a Theoretical Foundation of Policy Optimization for Learning Control Policies

10 October 2022

Na Li

Papers citing "Towards a Theoretical Foundation of Policy Optimization for Learning Control Policies"

7 / 7 papers shown

Title
Neural Operators of Backstepping Controller and Observer Gain Functions for Reaction-Diffusion PDEs Miroslav Krstic Luke Bhan Yuanyuan Shi 26 28 0 18 Mar 2023
Statistical Learning Theory for Control: A Finite Sample Perspective Anastasios Tsiamis Ingvar M. Ziemann Nikolai Matni George J. Pappas 13 73 0 12 Sep 2022
Stabilizing Dynamical Systems via Policy Gradient Methods Juan C. Perdomo Jack Umenberger Max Simchowitz 19 44 0 13 Oct 2021
On the Sample Complexity of Stability Constrained Imitation Learning Stephen Tu Alexander Robey Tingnan Zhang Nikolai Matni 41 38 0 18 Feb 2021
Robust Reinforcement Learning: A Case Study in Linear Quadratic Regulation Bo Pang Zhong-Ping Jiang 19 34 0 25 Aug 2020
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 119 1,190 0 16 Aug 2016
Calculus of the exponent of Kurdyka-Łojasiewicz inequality and its applications to linear convergence of first-order methods Guoyin Li Ting Kei Pong 95 288 0 09 Feb 2016