Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds

1 January 2019

Papers citing "Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds"

50 / 216 papers shown

Title
Toward Efficient Exploration by Large Language Model Agents Dilip Arumugam Thomas L. Griffiths LLMAG 94 1 0 29 Apr 2025
Minimax Optimal Reinforcement Learning with Quasi-Optimism Harin Lee Min-hwan Oh OffRL 64 0 0 02 Mar 2025
Hybrid Transfer Reinforcement Learning: Provable Sample Efficiency from Shifted-Dynamics Data Chengrui Qu Laixi Shi Kishan Panaganti Pengcheng You Adam Wierman OffRL OnRL 38 0 0 06 Nov 2024
Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous Agents Safwan Labbi D. Tiapkin Lorenzo Mancini Paul Mangold Eric Moulines FedML 73 0 0 30 Oct 2024
Truncating Trajectories in Monte Carlo Policy Evaluation: an Adaptive Approach Riccardo Poiani Nicole Nobili Alberto Maria Metelli Marcello Restelli 29 0 0 17 Oct 2024
How Does Variance Shape the Regret in Contextual Bandits? Zeyu Jia Jian Qian Alexander Rakhlin Chen-Yu Wei 35 4 0 16 Oct 2024
Can we hop in general? A discussion of benchmark selection and design using the Hopper environment C. Voelcker Marcel Hussing Eric Eaton OffRL 28 3 0 11 Oct 2024
Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition Zhong Zheng Haochen Zhang Lingzhou Xue OffRL 75 2 0 10 Oct 2024
State-free Reinforcement Learning Mingyu Chen Aldo Pacchiano Xuezhou Zhang 66 0 0 27 Sep 2024
Advances in Preference-based Reinforcement Learning: A Review Youssef Abdelkareem Shady Shehata Fakhri Karray OffRL 51 9 0 21 Aug 2024
Efficient Reinforcement Learning in Probabilistic Reward Machines Xiaofeng Lin Xuezhou Zhang 56 0 0 19 Aug 2024
Satisficing Exploration for Deep Reinforcement Learning Dilip Arumugam Saurabh Kumar Ramki Gummadi Benjamin Van Roy 42 1 0 16 Jul 2024
Warm-up Free Policy Optimization: Improved Regret in Linear Markov Decision Processes Asaf B. Cassel Aviv A. Rosenberg 40 1 0 03 Jul 2024
Combinatorial Multivariant Multi-Armed Bandits with Applications to Episodic Reinforcement Learning and Beyond Xutong Liu Siwei Wang Jinhang Zuo Han Zhong Xuchuang Wang Zhiyong Wang Shuai Li Mohammad Hajiesmaili J. C. Lui Wei Chen 85 1 0 03 Jun 2024
Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithm Miao Lu Han Zhong Tong Zhang Jose H. Blanchet OffRL OOD 76 4 0 04 Apr 2024
Utilizing Maximum Mean Discrepancy Barycenter for Propagating the Uncertainty of Value Functions in Reinforcement Learning Srinjoy Roy Swagatam Das 27 0 0 31 Mar 2024
Multiple-policy Evaluation via Density Estimation Yilei Chen Aldo Pacchiano I. Paschalidis OffRL 24 0 0 29 Mar 2024
The Value of Reward Lookahead in Reinforcement Learning Nadav Merlis Dorian Baudry Vianney Perchet 29 0 0 18 Mar 2024
Horizon-Free Regret for Linear Markov Decision Processes Zihan Zhang Jason D. Lee Yuxin Chen Simon S. Du 33 3 0 15 Mar 2024
On the Limited Representational Power of Value Functions and its Links to Statistical (In)Efficiency David Cheikhi Daniel Russo OffRL 33 0 0 11 Mar 2024
Scale-free Adversarial Reinforcement Learning Mingyu Chen Xuezhou Zhang 82 2 0 01 Mar 2024
Truly No-Regret Learning in Constrained MDPs Adrian Müller Pragnya Alatur V. Cevher Giorgia Ramponi Niao He 32 7 0 24 Feb 2024
More Benefits of Being Distributional: Second-Order Bounds for Reinforcement Learning Kaiwen Wang Owen Oertell Alekh Agarwal Nathan Kallus Wen Sun OffRL 88 12 0 11 Feb 2024
Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints Dan Qiao Yu-Xiang Wang OffRL 24 3 0 02 Feb 2024
Graph Attention-based Reinforcement Learning for Trajectory Design and Resource Assignment in Multi-UAV Assisted Communication Zikai Feng Diyang Wu Mengxing Huang Chau Yuen 26 8 0 31 Jan 2024
Cascading Reinforcement Learning Yihan Du R. Srikant Wei Chen 19 0 0 17 Jan 2024
MOTO: Offline Pre-training to Online Fine-tuning for Model-based Robot Learning Rafael Rafailov Kyle Hatch Victor Kolev John D. Martin Mariano Phielipp Chelsea Finn OffRL OnRL 22 9 0 06 Jan 2024
Rethinking Model-based, Policy-based, and Value-based Reinforcement Learning via the Lens of Representation Complexity Guhao Feng Han Zhong OffRL 76 2 0 28 Dec 2023
Sample Efficient Reinforcement Learning with Partial Dynamics Knowledge Meshal Alharbi Mardavij Roozbehani M. Dahleh 29 0 0 19 Dec 2023
Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation Jiayi Huang Han Zhong Liwei Wang Lin F. Yang 35 2 0 07 Dec 2023
On Representation Complexity of Model-based and Model-free Reinforcement Learning Hanlin Zhu Baihe Huang Stuart Russell OffRL 33 3 0 03 Oct 2023
Learning to Make Adherence-Aware Advice Guanting Chen Xiaocheng Li Chunlin Sun Hanzhao Wang 30 10 0 01 Oct 2023
Settling the Sample Complexity of Online Reinforcement Learning Zihan Zhang Yuxin Chen Jason D. Lee S. Du OffRL 98 21 0 25 Jul 2023
Policy Finetuning in Reinforcement Learning via Design of Experiments using Offline Data Ruiqi Zhang Andrea Zanette OffRL OnRL 40 7 0 10 Jul 2023
Sharper Model-free Reinforcement Learning for Average-reward Markov Decision Processes Zihan Zhang Qiaomin Xie OffRL 26 17 0 28 Jun 2023
Active Coverage for PAC Reinforcement Learning Aymen Al Marjani Andrea Tirinzoni E. Kaufmann OffRL 21 4 0 23 Jun 2023
Optimal Exploration for Model-Based RL in Nonlinear Systems Andrew Wagenmaker Guanya Shi Kevin G. Jamieson 36 14 0 15 Jun 2023
Cancellation-Free Regret Bounds for Lagrangian Approaches in Constrained Markov Decision Processes A. Müller Pragnya Alatur Giorgia Ramponi Niao He 25 5 0 12 Jun 2023
Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds Jiayi Huang Han Zhong Liwei Wang Lin F. Yang 24 6 0 12 Jun 2023
Near-optimal Conservative Exploration in Reinforcement Learning under Episode-wise Constraints Donghao Li Ruiquan Huang Cong Shen Jing Yang 32 3 0 09 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 33 0 0 02 Jun 2023
The Benefits of Being Distributional: Small-Loss Bounds for Reinforcement Learning Kaiwen Wang Kevin Zhou Runzhe Wu Nathan Kallus Wen Sun OffRL 31 17 0 25 May 2023
Replicable Reinforcement Learning Eric Eaton Marcel Hussing Michael Kearns Jessica Sorrell OffRL 32 13 0 24 May 2023
Bayesian Reinforcement Learning with Limited Cognitive Load Dilip Arumugam Mark K. Ho Noah D. Goodman Benjamin Van Roy OffRL 34 8 0 05 May 2023
Posterior Sampling for Deep Reinforcement Learning Remo Sasso Michelangelo Conserva Paulo E. Rauber OffRL BDL 37 6 0 30 Apr 2023
Provably Feedback-Efficient Reinforcement Learning via Active Reward Learning Dingwen Kong Lin F. Yang 34 9 0 18 Apr 2023
Minimax-Optimal Reward-Agnostic Exploration in Reinforcement Learning Gen Li Yuling Yan Yuxin Chen Jianqing Fan OffRL 76 12 0 14 Apr 2023
Restarted Bayesian Online Change-point Detection for Non-Stationary Markov Decision Processes Réda Alami Mohammed Mahfoud Eric Moulines 22 2 0 01 Apr 2023
Act-Then-Measure: Reinforcement Learning for Partially Observable Environments with Active Measuring Merlijn Krale T. D. Simão N. Jansen OffRL 10 7 0 14 Mar 2023
Fast Rates for Maximum Entropy Exploration D. Tiapkin Denis Belomestny Daniele Calandriello Eric Moulines Rémi Munos A. Naumov Pierre Perrault Yunhao Tang Michal Valko Pierre Menard 44 17 0 14 Mar 2023