Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems

24 June 2022

Papers citing "Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems"

24 / 24 papers shown

Title
The Sample Complexity of Online Strategic Decision Making with Information Asymmetry and Knowledge Transportability Jiachen Hu Rui Ai Han Zhong Xiaoyu Chen L. Wang Zhaoran Wang Zhuoran Yang 65 0 0 11 Jun 2025
Transformers as Multi-task Learners: Decoupling Features in Hidden Markov Models Yifan Hao Chenlu Ye Chi Han Tong Zhang 63 0 0 02 Jun 2025
Statistical Tractability of Off-policy Evaluation of History-dependent Policies in POMDPs Yuheng Zhang Nan Jiang OffRL 87 0 0 03 Mar 2025
Diffusion Spectral Representation for Reinforcement Learning Dmitry Shribak Chen-Xiao Gao Yitong Li Chenjun Xiao Bo Dai DiffM 109 5 0 23 Jun 2024
RL in Latent MDPs is Tractable: Online Guarantees via Off-Policy Evaluation Jeongyeol Kwon Shie Mannor Constantine Caramanis Yonathan Efroni OffRL 109 3 0 03 Jun 2024
Regularized DeepIV with Model Selection Zihao Li Hui Lan Vasilis Syrgkanis Mengdi Wang Masatoshi Uehara 103 3 0 07 Mar 2024
On the Curses of Future and History in Future-dependent Value Functions for Off-policy Evaluation Yuheng Zhang Nan Jiang OffRL 67 4 0 22 Feb 2024
Safe Reinforcement Learning in Tensor Reproducing Kernel Hilbert Space Xiaoyuan Cheng Boli Chen Liz Varga Yukun Hu 40 0 0 01 Dec 2023
Provable Representation with Efficient Planning for Partial Observable Reinforcement Learning Hongming Zhang Zhaolin Ren Chenjun Xiao Dale Schuurmans Bo Dai 104 4 0 20 Nov 2023
Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes Ruiquan Huang Yuan Cheng Jing Yang Vincent Tan Yingbin Liang 77 0 0 20 Oct 2023
Prospective Side Information for Latent MDPs Jeongyeol Kwon Yonathan Efroni Shie Mannor Constantine Caramanis 78 6 0 11 Oct 2023
Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight Jiacheng Guo Minshuo Chen Haiquan Wang Caiming Xiong Mengdi Wang Yu Bai 90 5 0 06 Jul 2023
Provably Efficient UCB-type Algorithms For Learning Predictive State Representations Ruiquan Huang Yitao Liang J. Yang OffRL 118 5 0 01 Jul 2023
Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP Jiacheng Guo Zihao Li Huazheng Wang Mengdi Wang Zhuoran Yang Xuezhou Zhang 73 6 0 21 Jun 2023
Efficient Reinforcement Learning with Impaired Observability: Learning to Act with Delayed and Missing State Observations Minshuo Chen Jie Meng Yunru Bai Yinyu Ye H. Vincent Poor Mengdi Wang 80 0 0 02 Jun 2023
Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration Zhihan Liu Miao Lu Wei Xiong Han Zhong Haotian Hu Shenao Zhang Sirui Zheng Zhuoran Yang Zhaoran Wang OffRL 124 22 0 29 May 2023
Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPs Yuan Cheng Ruiquan Huang J. Yang Yitao Liang OffRL 74 8 0 20 Mar 2023
Can Direct Latent Model Learning Solve Linear Quadratic Gaussian Control? Yi Tian Kai Zhang Russ Tedrake S. Sra 85 5 0 30 Dec 2022
Reward-Mixing MDPs with a Few Latent Contexts are Learnable Jeongyeol Kwon Yonathan Efroni Constantine Caramanis Shie Mannor 81 5 0 05 Oct 2022
Partially Observable RL with B-Stability: Unified Structural Condition and Sharp Sample-Efficient Algorithms Fan Chen Yu Bai Song Mei 100 22 0 29 Sep 2022
Future-Dependent Value-Based Off-Policy Evaluation in POMDPs Masatoshi Uehara Haruka Kiyohara Andrew Bennett Victor Chernozhukov Nan Jiang Nathan Kallus C. Shi Wen Sun OffRL 88 20 0 26 Jul 2022
PAC Reinforcement Learning for Predictive State Representations Wenhao Zhan Masatoshi Uehara Wen Sun Jason D. Lee 90 39 0 12 Jul 2022
Computationally Efficient PAC RL in POMDPs with Latent Determinism and Conditional Embeddings Masatoshi Uehara Ayush Sekhari Jason D. Lee Nathan Kallus Wen Sun 95 6 0 24 Jun 2022
Finite-Time Analysis of Natural Actor-Critic for POMDPs Semih Cayci Niao He R. Srikant 66 3 0 20 Feb 2022