Learning in Observable POMDPs, without Computationally Intractable Oracles

7 June 2022

Papers citing "Learning in Observable POMDPs, without Computationally Intractable Oracles"

7 / 7 papers shown

Title
A Model Selection Approach for Corruption Robust Reinforcement Learning Chen-Yu Wei Christoph Dann Julian Zimmert 85 44 0 31 Dec 2024
Provable Representation with Efficient Planning for Partial Observable Reinforcement Learning Hongming Zhang Tongzheng Ren Chenjun Xiao Dale Schuurmans Bo Dai 45 3 0 20 Nov 2023
Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP Jiacheng Guo Zihao Li Huazheng Wang Mengdi Wang Zhuoran Yang Xuezhou Zhang 32 5 0 21 Jun 2023
Reward-Mixing MDPs with a Few Latent Contexts are Learnable Jeongyeol Kwon Yonathan Efroni C. Caramanis Shie Mannor 29 5 0 05 Oct 2022
PAC Reinforcement Learning for Predictive State Representations Wenhao Zhan Masatoshi Uehara Wen Sun Jason D. Lee 31 38 0 12 Jul 2022
Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems Masatoshi Uehara Ayush Sekhari Jason D. Lee Nathan Kallus Wen Sun OffRL 49 31 0 24 Jun 2022
Reward-Free Exploration for Reinforcement Learning Chi Jin A. Krishnamurthy Max Simchowitz Tiancheng Yu OffRL 112 194 0 07 Feb 2020