Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium
Learning from Offline Datasets

Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets

15 February 2022

Wei Xiong

Tong Zhang

Papers citing "Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets"

10 / 10 papers shown

Title
Reinforcement Learning with Human Feedback: Learning Dynamic Choices via Pessimism Zihao Li Zhuoran Yang Mengdi Wang OffRL 29 52 0 29 May 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 37 29 0 16 May 2023
Offline Learning in Markov Games with General Function Approximation Yuheng Zhang Yunru Bai Nan Jiang OffRL 13 8 0 06 Feb 2023
Minimax-Optimal Multi-Agent RL in Markov Games With a Generative Model Gen Li Yuejie Chi Yuting Wei Yuxin Chen 20 18 0 22 Aug 2022
Offline Equilibrium Finding Shuxin Li Xinrun Wang Youzhi Zhang Jakub Cerny Pengdeng Li Hau Chan Bo An OffRL 34 2 0 12 Jul 2022
The Complexity of Markov Equilibrium in Stochastic Games C. Daskalakis Noah Golowich K. Zhang 29 57 0 08 Apr 2022
When is Offline Two-Player Zero-Sum Markov Game Solvable? Qiwen Cui S. Du OffRL 23 29 0 10 Jan 2022
Pessimistic Model-based Offline Reinforcement Learning under Partial Coverage Masatoshi Uehara Wen Sun OffRL 91 33 0 13 Jul 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
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems Sergey Levine Aviral Kumar George Tucker Justin Fu OffRL GP 329 1,949 0 04 May 2020