Optimistic Policy Optimization is Provably Efficient in Non-stationary MDPs

18 October 2021

Papers citing "Optimistic Policy Optimization is Provably Efficient in Non-stationary MDPs"

8 / 8 papers shown

Title
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes Han Zhong Tong Zhang 30 26 0 15 May 2023
Doubly Inhomogeneous Reinforcement Learning Liyuan Hu Mengbing Li C. Shi Zhanghua Wu Piotr Fryzlewicz OffRL 27 2 0 08 Nov 2022
Testing Stationarity and Change Point Detection in Reinforcement Learning Mengbing Li C. Shi Zhanghua Wu Piotr Fryzlewicz OffRL 37 9 0 03 Mar 2022
Nearly Optimal Policy Optimization with Stable at Any Time Guarantee Tianhao Wu Yunchang Yang Han Zhong Liwei Wang S. Du Jiantao Jiao 45 14 0 21 Dec 2021
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints Chi Jin Zhuoran Yang Zhaoran Wang OffRL 107 166 0 06 Jan 2021
Efficient Learning in Non-Stationary Linear Markov Decision Processes Ahmed Touati Pascal Vincent 32 29 0 24 Oct 2020
Optimism in Reinforcement Learning with Generalized Linear Function Approximation Yining Wang Ruosong Wang S. Du A. Krishnamurthy 127 135 0 09 Dec 2019
Weighted Linear Bandits for Non-Stationary Environments Yoan Russac Claire Vernade Olivier Cappé 82 101 0 19 Sep 2019