Towards Theoretical Understandings of Robust Markov Decision Processes:
Sample Complexity and Asymptotics

Towards Theoretical Understandings of Robust Markov Decision Processes: Sample Complexity and Asymptotics

9 May 2021

Wenhao Yang

Papers citing "Towards Theoretical Understandings of Robust Markov Decision Processes: Sample Complexity and Asymptotics"

10 / 10 papers shown

Title
Constrained Reinforcement Learning Under Model Mismatch Zhongchang Sun Sihong He Fei Miao Shaofeng Zou 44 4 0 02 May 2024
Distributionally Robust Model-based Reinforcement Learning with Large State Spaces Shyam Sundhar Ramesh Pier Giuseppe Sessa Yifan Hu Andreas Krause Ilija Bogunovic OOD 42 10 0 05 Sep 2023
Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage Jose H. Blanchet Miao Lu Tong Zhang Han Zhong OffRL 42 29 0 16 May 2023
Improved Sample Complexity Bounds for Distributionally Robust Reinforcement Learning Zaiyan Xu Kishan Panaganti D. Kalathil OOD OffRL 29 30 0 05 Mar 2023
A Finite Sample Complexity Bound for Distributionally Robust Q-learning Shengbo Wang Nian Si Jose H. Blanchet Zhengyuan Zhou OOD OffRL 32 22 0 26 Feb 2023
Robust Average-Reward Markov Decision Processes Yue Wang Alvaro Velasquez George K. Atia Ashley Prater-Bennette Shaofeng Zou 33 11 0 02 Jan 2023
Distributionally Robust Offline Reinforcement Learning with Linear Function Approximation Xiaoteng Ma Zhipeng Liang Jose H. Blanchet MingWen Liu Li Xia Jiheng Zhang Qianchuan Zhao Zhengyuan Zhou OOD OffRL 38 22 0 14 Sep 2022
A Statistical Analysis of Polyak-Ruppert Averaged Q-learning Xiang Li Wenhao Yang Jiadong Liang Zhihua Zhang Michael I. Jordan 37 15 0 29 Dec 2021
Sample Complexity of Robust Reinforcement Learning with a Generative Model Kishan Panaganti D. Kalathil 93 69 0 02 Dec 2021
Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes Nathan Kallus Masatoshi Uehara OffRL 38 181 0 22 Aug 2019