Planning in Observable POMDPs in Quasipolynomial Time

12 January 2022

Papers citing "Planning in Observable POMDPs in Quasipolynomial Time"

20 / 20 papers shown

Title
Statistical Tractability of Off-policy Evaluation of History-dependent Policies in POMDPs Yuheng Zhang Nan Jiang OffRL 61 0 0 03 Mar 2025
The Limits of Pure Exploration in POMDPs: When the Observation Entropy is Enough Riccardo Zamboni Duilio Cirino Marcello Restelli Mirco Mutti 41 4 0 18 Jun 2024
On Limitation of Transformer for Learning HMMs Jiachen Hu Qinghua Liu Chi Jin 47 3 0 06 Jun 2024
How to Explore with Belief: State Entropy Maximization in POMDPs Riccardo Zamboni Duilio Cirino Marcello Restelli Mirco Mutti 39 3 0 04 Jun 2024
Provably Efficient Partially Observable Risk-Sensitive Reinforcement Learning with Hindsight Observation Tonghe Zhang Yu Chen Longbo Huang 38 0 0 28 Feb 2024
SayCanPay: Heuristic Planning with Large Language Models using Learnable Domain Knowledge Rishi Hazra Pedro Zuidberg Dos Martires Luc de Raedt LM&Ro LLMAG 18 31 0 24 Aug 2023
Provably Efficient UCB-type Algorithms For Learning Predictive State Representations Ruiquan Huang Yitao Liang J. Yang OffRL 24 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 32 5 0 21 Jun 2023
Theoretical Hardness and Tractability of POMDPs in RL with Partial Online State Information Ming Shi Yingbin Liang Ness B. Shroff 29 2 0 14 Jun 2023
Exponential Hardness of Reinforcement Learning with Linear Function Approximation Daniel M. Kane Sihan Liu Shachar Lovett G. Mahajan Csaba Szepesvári Gellert Weisz 46 3 0 25 Feb 2023
Learning in POMDPs is Sample-Efficient with Hindsight Observability Jonathan Lee Alekh Agarwal Christoph Dann Tong Zhang 31 19 0 31 Jan 2023
Partially Observable RL with B-Stability: Unified Structural Condition and Sharp Sample-Efficient Algorithms Fan Chen Yu Bai Song Mei 53 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 29 16 0 26 Jul 2022
PAC Reinforcement Learning for Predictive State Representations Wenhao Zhan Masatoshi Uehara Wen Sun Jason D. Lee 31 38 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 58 6 0 24 Jun 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
Learning in Observable POMDPs, without Computationally Intractable Oracles Noah Golowich Ankur Moitra Dhruv Rohatgi 26 26 0 07 Jun 2022
Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency Qi Cai Zhuoran Yang Zhaoran Wang 30 13 0 20 Apr 2022
When Is Partially Observable Reinforcement Learning Not Scary? Qinghua Liu Alan Chung Csaba Szepesvári Chi Jin 14 92 0 19 Apr 2022
Convergence of Finite Memory Q-Learning for POMDPs and Near Optimality of Learned Policies under Filter Stability A. D. Kara S. Yüksel 19 31 0 22 Mar 2021