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
Nearly Minimax Optimal Reinforcement Learning for Linear Mixture Markov Decision Processes Dongruo Zhou Quanquan Gu Csaba Szepesvári 19 203 0 15 Dec 2020
Minimax Regret for Stochastic Shortest Path with Adversarial Costs and Known Transition Liyu Chen Haipeng Luo Chen-Yu Wei 26 32 0 07 Dec 2020
Accommodating Picky Customers: Regret Bound and Exploration Complexity for Multi-Objective Reinforcement Learning Jingfeng Wu Vladimir Braverman Lin F. Yang 17 10 0 25 Nov 2020
Logarithmic Regret for Reinforcement Learning with Linear Function Approximation Jiafan He Dongruo Zhou Quanquan Gu 17 92 0 23 Nov 2020
Value Function Approximations via Kernel Embeddings for No-Regret Reinforcement Learning Sayak Ray Chowdhury Rafael Oliveira OffRL 17 3 0 16 Nov 2020
Experimental Design for Regret Minimization in Linear Bandits Andrew Wagenmaker Julian Katz-Samuels Kevin G. Jamieson 9 16 0 01 Nov 2020
Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration Priyank Agrawal Jinglin Chen Nan Jiang 27 18 0 23 Oct 2020
Local Differential Privacy for Regret Minimization in Reinforcement Learning Evrard Garcelon Vianney Perchet Ciara Pike-Burke Matteo Pirotta 26 32 0 15 Oct 2020
Nearly Minimax Optimal Reward-free Reinforcement Learning Zihan Zhang S. Du Xiangyang Ji OffRL 17 31 0 12 Oct 2020
Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited O. D. Domingues Pierre Ménard E. Kaufmann Michal Valko 8 96 0 07 Oct 2020
Nearly Minimax Optimal Reinforcement Learning for Discounted MDPs Jiafan He Dongruo Zhou Quanquan Gu 16 37 0 01 Oct 2020
Is Reinforcement Learning More Difficult Than Bandits? A Near-optimal Algorithm Escaping the Curse of Horizon Zihan Zhang Xiangyang Ji S. Du OffRL 12 103 0 28 Sep 2020
A Sample-Efficient Algorithm for Episodic Finite-Horizon MDP with Constraints K. C. Kalagarla Rahul Jain Pierluigi Nuzzo 28 52 0 23 Sep 2020
Oracle-Efficient Regret Minimization in Factored MDPs with Unknown Structure Aviv A. Rosenberg Yishay Mansour 15 11 0 13 Sep 2020
Improved Exploration in Factored Average-Reward MDPs M. S. Talebi Anders Jonsson Odalric-Ambrym Maillard 9 8 0 09 Sep 2020
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration Andrea Zanette A. Lazaric Mykel J. Kochenderfer Emma Brunskill 24 64 0 18 Aug 2020
Reinforcement Learning with Trajectory Feedback Yonathan Efroni Nadav Merlis Shie Mannor 14 41 0 13 Aug 2020
Fast active learning for pure exploration in reinforcement learning Pierre Ménard O. D. Domingues Anders Jonsson E. Kaufmann Edouard Leurent Michal Valko 6 94 0 27 Jul 2020
A Provably Efficient Sample Collection Strategy for Reinforcement Learning Jean Tarbouriech Matteo Pirotta Michal Valko A. Lazaric OffRL 25 16 0 13 Jul 2020
A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces O. D. Domingues Pierre Ménard Matteo Pirotta E. Kaufmann Michal Valko 25 40 0 09 Jul 2020
A Unifying View of Optimism in Episodic Reinforcement Learning Gergely Neu Ciara Pike-Burke 6 66 0 03 Jul 2020
Adaptive Discretization for Model-Based Reinforcement Learning Sean R. Sinclair Tianyu Wang Gauri Jain Siddhartha Banerjee Chao Yu OffRL 19 21 0 01 Jul 2020
Model-based Reinforcement Learning: A Survey Thomas M. Moerland Joost Broekens Aske Plaat Catholijn M. Jonker OffRL 33 47 0 30 Jun 2020
Lookahead-Bounded Q-Learning Ibrahim El Shar Daniel R. Jiang VLM 16 8 0 28 Jun 2020
Towards Minimax Optimal Reinforcement Learning in Factored Markov Decision Processes Yi Tian Jian Qian S. Sra 8 25 0 24 Jun 2020
Stochastic Shortest Path with Adversarially Changing Costs Aviv A. Rosenberg Yishay Mansour AAML 24 33 0 20 Jun 2020
Provably adaptive reinforcement learning in metric spaces Tongyi Cao A. Krishnamurthy 17 7 0 18 Jun 2020
Task-agnostic Exploration in Reinforcement Learning Xuezhou Zhang Yuzhe Ma Adish Singla OffRL 20 49 0 16 Jun 2020
$Q$ -learning with Logarithmic Regret Kunhe Yang Lin F. Yang S. Du 43 59 0 16 Jun 2020
Preference-based Reinforcement Learning with Finite-Time Guarantees Yichong Xu Ruosong Wang Lin F. Yang Aarti Singh A. Dubrawski 23 53 0 16 Jun 2020
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning Sebastian Curi Felix Berkenkamp Andreas Krause 33 82 0 15 Jun 2020
Adaptive Reward-Free Exploration E. Kaufmann Pierre Ménard O. D. Domingues Anders Jonsson Edouard Leurent Michal Valko 30 80 0 11 Jun 2020
Planning in Markov Decision Processes with Gap-Dependent Sample Complexity Anders Jonsson E. Kaufmann Pierre Ménard O. D. Domingues Edouard Leurent Michal Valko 9 31 0 10 Jun 2020
A Model-free Learning Algorithm for Infinite-horizon Average-reward MDPs with Near-optimal Regret Mehdi Jafarnia-Jahromi Chen-Yu Wei Rahul Jain Haipeng Luo 20 7 0 08 Jun 2020
MOPO: Model-based Offline Policy Optimization Tianhe Yu G. Thomas Lantao Yu Stefano Ermon James Zou Sergey Levine Chelsea Finn Tengyu Ma OffRL 25 754 0 27 May 2020
Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension Ruosong Wang Ruslan Salakhutdinov Lin F. Yang 23 55 0 21 May 2020
Reinforcement Learning with Feedback Graphs Christoph Dann Yishay Mansour M. Mohri Ayush Sekhari Karthik Sridharan 14 9 0 07 May 2020
Is Long Horizon Reinforcement Learning More Difficult Than Short Horizon Reinforcement Learning? Ruosong Wang S. Du Lin F. Yang Sham Kakade OffRL 10 52 0 01 May 2020
Almost Optimal Model-Free Reinforcement Learning via Reference-Advantage Decomposition Zihan Zhang Yuanshuo Zhou Xiangyang Ji OffRL 8 155 0 21 Apr 2020
Tightening Exploration in Upper Confidence Reinforcement Learning Hippolyte Bourel Odalric-Ambrym Maillard M. S. Talebi 22 31 0 20 Apr 2020
Kernel-Based Reinforcement Learning: A Finite-Time Analysis O. D. Domingues Pierre Ménard Matteo Pirotta E. Kaufmann Michal Valko 9 18 0 12 Apr 2020
Is Temporal Difference Learning Optimal? An Instance-Dependent Analysis K. Khamaru A. Pananjady Feng Ruan Martin J. Wainwright Michael I. Jordan OffRL 11 47 0 16 Mar 2020
Provably Efficient Exploration for Reinforcement Learning Using Unsupervised Learning Fei Feng Ruosong Wang W. Yin S. Du Lin F. Yang OffRL SSL 30 7 0 15 Mar 2020
Exploration-Exploitation in Constrained MDPs Yonathan Efroni Shie Mannor Matteo Pirotta 33 169 0 04 Mar 2020
Learning Near Optimal Policies with Low Inherent Bellman Error Andrea Zanette A. Lazaric Mykel Kochenderfer Emma Brunskill OffRL 17 221 0 29 Feb 2020
Near-optimal Regret Bounds for Stochastic Shortest Path Alon Cohen Haim Kaplan Yishay Mansour Aviv A. Rosenberg 12 53 0 23 Feb 2020
Optimistic Policy Optimization with Bandit Feedback Yonathan Efroni Lior Shani Aviv A. Rosenberg Shie Mannor 13 90 0 19 Feb 2020
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium Qiaomin Xie Yudong Chen Zhaoran Wang Zhuoran Yang 39 124 0 17 Feb 2020
Regret Bounds for Discounted MDPs Shuang Liu H. Su OffRL 8 19 0 12 Feb 2020
Provable Self-Play Algorithms for Competitive Reinforcement Learning Yu Bai Chi Jin SSL 22 148 0 10 Feb 2020