RL for Latent MDPs: Regret Guarantees and a Lower Bound

9 February 2021

Papers citing "RL for Latent MDPs: Regret Guarantees and a Lower Bound"

50 / 57 papers shown

Title
Model-based controller assisted domain randomization in deep reinforcement learning: application to nonlinear powertrain control Heisei Yonezawa Ansei Yonezawa Itsuro Kajiwara 36 0 0 28 Apr 2025
Improving Controller Generalization with Dimensionless Markov Decision Processes V. Charvet Sebastian Stein R. Murray-Smith 34 0 0 14 Apr 2025
A Classification View on Meta Learning Bandits Mirco Mutti Jeongyeol Kwon Shie Mannor Aviv Tamar 23 0 0 06 Apr 2025
Statistical Tractability of Off-policy Evaluation of History-dependent Policies in POMDPs Yuheng Zhang Nan Jiang OffRL 61 0 0 03 Mar 2025
Personalized and Sequential Text-to-Image Generation Ofir Nabati Guy Tennenholtz ChihWei Hsu Moonkyung Ryu Deepak Ramachandran Yinlam Chow Xiang Li Craig Boutilier MLLM 77 0 0 10 Dec 2024
Learning to Cooperate with Humans using Generative Agents Yancheng Liang Daphne Chen Abhishek Gupta S. Du Natasha Jaques SyDa 77 4 0 21 Nov 2024
Hybrid Transfer Reinforcement Learning: Provable Sample Efficiency from Shifted-Dynamics Data Chengrui Qu Laixi Shi Kishan Panaganti Pengcheng You Adam Wierman OffRL OnRL 36 0 0 06 Nov 2024
Learning in Markov Games with Adaptive Adversaries: Policy Regret, Fundamental Barriers, and Efficient Algorithms Thanh Nguyen-Tang Raman Arora 74 1 0 01 Nov 2024
Test-Time Regret Minimization in Meta Reinforcement Learning Mirco Mutti Aviv Tamar 23 4 0 04 Jun 2024
RL in Latent MDPs is Tractable: Online Guarantees via Off-Policy Evaluation Jeongyeol Kwon Shie Mannor C. Caramanis Yonathan Efroni OffRL 37 2 0 03 Jun 2024
A CMDP-within-online framework for Meta-Safe Reinforcement Learning Vanshaj Khattar Yuhao Ding Bilgehan Sel Javad Lavaei Ming Jin OffRL 32 12 0 26 May 2024
Pausing Policy Learning in Non-stationary Reinforcement Learning Hyunin Lee Ming Jin Javad Lavaei Somayeh Sojoudi OffRL 34 2 0 25 May 2024
Preparing for Black Swans: The Antifragility Imperative for Machine Learning Ming Jin 36 2 0 18 May 2024
DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning Anthony Liang Guy Tennenholtz Chih-Wei Hsu Yinlam Chow Erdem Biyik Craig Boutilier OffRL 38 1 0 25 Feb 2024
On the Curses of Future and History in Future-dependent Value Functions for Off-policy Evaluation Yuheng Zhang Nan Jiang OffRL 27 4 0 22 Feb 2024
Weakly Coupled Deep Q-Networks Ibrahim El Shar Daniel R. Jiang 19 2 0 28 Oct 2023
Prospective Side Information for Latent MDPs Jeongyeol Kwon Yonathan Efroni Shie Mannor C. Caramanis 23 5 0 11 Oct 2023
Tempo Adaptation in Non-stationary Reinforcement Learning Hyunin Lee Yuhao Ding Jongmin Lee Ming Jin Javad Lavaei Somayeh Sojoudi 9 3 0 26 Sep 2023
JoinGym: An Efficient Query Optimization Environment for Reinforcement Learning Kaiwen Wang Junxiong Wang Yueying Li Nathan Kallus Immanuel Trummer Wen Sun GP 44 2 0 21 Jul 2023
Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight Jiacheng Guo Minshuo Chen Haiquan Wang Caiming Xiong Mengdi Wang Yu Bai 19 5 0 06 Jul 2023
Provably Efficient UCB-type Algorithms For Learning Predictive State Representations Ruiquan Huang Yitao Liang J. Yang OffRL 24 5 0 01 Jul 2023
Context-lumpable stochastic bandits Chung-Wei Lee Qinghua Liu Yasin Abbasi-Yadkori Chi Jin Tor Lattimore Csaba Szepesvári OffRL 100 2 0 22 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
Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources Chengshuai Shi Wei Xiong Cong Shen Jing Yang OffRL 30 3 0 14 Jun 2023
Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition Yash Chandak S. Thakoor Z. Guo Yunhao Tang Rémi Munos Will Dabney Diana Borsa 13 2 0 01 May 2023
Hardness of Independent Learning and Sparse Equilibrium Computation in Markov Games Dylan J. Foster Noah Golowich Sham Kakade 20 10 0 22 Mar 2023
POPGym: Benchmarking Partially Observable Reinforcement Learning Steven D. Morad Ryan Kortvelesy Matteo Bettini Stephan Liwicki Amanda Prorok OffRL 14 37 0 03 Mar 2023
Reinforcement Learning with History-Dependent Dynamic Contexts Guy Tennenholtz Nadav Merlis Lior Shani Martin Mladenov Craig Boutilier AI4CE 11 6 0 04 Feb 2023
Learning in POMDPs is Sample-Efficient with Hindsight Observability Jonathan Lee Alekh Agarwal Christoph Dann Tong Zhang 26 19 0 31 Jan 2023
Adversarial Online Multi-Task Reinforcement Learning Quan Nguyen Nishant A. Mehta 14 1 0 11 Jan 2023
An Instrumental Variable Approach to Confounded Off-Policy Evaluation Yang Xu Jin Zhu C. Shi S. Luo R. Song OffRL 21 12 0 29 Dec 2022
Offline Policy Evaluation and Optimization under Confounding Chinmaya Kausik Yangyi Lu Kevin Tan Maggie Makar Yixin Wang Ambuj Tewari OffRL 18 8 0 29 Nov 2022
Learning Mixtures of Markov Chains and MDPs Chinmaya Kausik Kevin Tan Ambuj Tewari 13 11 0 17 Nov 2022
Group Distributionally Robust Reinforcement Learning with Hierarchical Latent Variables Mengdi Xu Peide Huang Yaru Niu Visak C. V. Kumar Jielin Qiu ... Kuan-Hui Lee Xuewei Qi H. Lam Bo-wen Li Ding Zhao OOD 54 9 0 21 Oct 2022
Horizon-Free and Variance-Dependent Reinforcement Learning for Latent Markov Decision Processes Runlong Zhou Ruosong Wang S. Du 31 3 0 20 Oct 2022
Tractable Optimality in Episodic Latent MABs Jeongyeol Kwon Yonathan Efroni C. Caramanis Shie Mannor 50 3 0 05 Oct 2022
Reward-Mixing MDPs with a Few Latent Contexts are Learnable Jeongyeol Kwon Yonathan Efroni C. Caramanis Shie Mannor 29 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 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
On the Complexity of Adversarial Decision Making Dylan J. Foster Alexander Rakhlin Ayush Sekhari Karthik Sridharan AAML 21 28 0 27 Jun 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 24 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
Model-Free and Model-Based Policy Evaluation when Causality is Uncertain David Bruns-Smith CML ELM OffRL 22 12 0 02 Apr 2022
Learning Markov Games with Adversarial Opponents: Efficient Algorithms and Fundamental Limits Qinghua Liu Yuanhao Wang Chi Jin AAML 24 15 0 14 Mar 2022
Understanding Curriculum Learning in Policy Optimization for Online Combinatorial Optimization Runlong Zhou Zelin He Yuandong Tian Yi Wu S. Du OffRL 18 3 0 11 Feb 2022
The Importance of Non-Markovianity in Maximum State Entropy Exploration Mirco Mutti Ric De Santi Marcello Restelli 30 31 0 07 Feb 2022