Is Q-learning Provably Efficient?

10 July 2018

Papers citing "Is Q-learning Provably Efficient?"

50 / 222 papers shown

Title
Automatic Reward Shaping from Confounded Offline Data Mingxuan Li Junzhe Zhang Elias Bareinboim OffRL OnRL 39 0 0 16 May 2025
Exploration by Random Distribution Distillation Zhirui Fang Kai Yang Jian Tao Jiafei Lyu Lusong Li Li Shen Xiu Li 16 0 0 16 May 2025
Toward Efficient Exploration by Large Language Model Agents Dilip Arumugam Thomas L. Griffiths LLMAG 94 1 0 29 Apr 2025
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model Moritz A. Zanger Pascal R. van der Vaart Wendelin Bohmer M. Spaan UQCV BDL 251 0 0 14 Mar 2025
Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF Shicong Cen Jincheng Mei Katayoon Goshvadi Hanjun Dai Tong Yang Sherry Yang Dale Schuurmans Yuejie Chi Bo Dai OffRL 70 24 0 20 Feb 2025
Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games Tong Yang Bo Dai Lin Xiao Yuejie Chi OffRL 69 2 0 13 Feb 2025
RL-STaR: Theoretical Analysis of Reinforcement Learning Frameworks for Self-Taught Reasoner Fu-Chieh Chang Yu-Ting Lee Hui-Ying Shih Pei-Yuan Wu Pei-Yuan Wu OffRL LRM 243 0 0 31 Oct 2024
Provably Efficient Exploration in Inverse Constrained Reinforcement Learning Bo Yue Jian Li Guiliang Liu 39 2 0 24 Sep 2024
Leveraging Unlabeled Data Sharing through Kernel Function Approximation in Offline Reinforcement Learning Yen-Ru Lai Fu-Chieh Chang Pei-Yuan Wu OffRL 84 1 0 22 Aug 2024
Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation Taehyun Cho Seung Han Kyungjae Lee Seokhun Ju Dohyeong Kim Jungwoo Lee 72 0 0 31 Jul 2024
Optimistic Q-learning for average reward and episodic reinforcement learning Priyank Agrawal Shipra Agrawal 60 4 0 18 Jul 2024
Learning to Steer Markovian Agents under Model Uncertainty Jiawei Huang Vinzenz Thoma Zebang Shen H. Nax Niao He 52 2 0 14 Jul 2024
Narrowing the Gap between Adversarial and Stochastic MDPs via Policy Optimization D. Tiapkin Evgenii Chzhen Gilles Stoltz 74 1 0 08 Jul 2024
Reinforcement Learning from Human Feedback without Reward Inference: Model-Free Algorithm and Instance-Dependent Analysis Qining Zhang Honghao Wei Lei Ying OffRL 67 1 0 11 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 79 6 0 04 Apr 2024
Horizon-Free Regret for Linear Markov Decision Processes Zihan Zhang Jason D. Lee Yuxin Chen Simon S. Du 35 3 0 15 Mar 2024
Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation Yu Chen Xiangcheng Zhang Siwei Wang Longbo Huang 47 3 0 28 Feb 2024
Enhancing Reinforcement Learning Agents with Local Guides Paul Daoudi Bogdan Robu Christophe Prieur Ludovic Dos Santos M. Barlier OnRL 31 3 0 21 Feb 2024
Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices Jiin Woo Laixi Shi Gauri Joshi Yuejie Chi OffRL 39 3 0 08 Feb 2024
Cascading Reinforcement Learning Yihan Du R. Srikant Wei Chen 19 0 0 17 Jan 2024
Conservative Exploration for Policy Optimization via Off-Policy Policy Evaluation Paul Daoudi Mathias Formoso Othman Gaizi Achraf Azize Evrard Garcelon OffRL 31 0 0 24 Dec 2023
Multi-Agent Probabilistic Ensembles with Trajectory Sampling for Connected Autonomous Vehicles Ruoqi Wen Jiahao Huang Rongpeng Li Guoru Ding Zhifeng Zhao 42 1 0 21 Dec 2023
A Concentration Bound for TD(0) with Function Approximation Siddharth Chandak Vivek Borkar 42 0 0 16 Dec 2023
The Effective Horizon Explains Deep RL Performance in Stochastic Environments Cassidy Laidlaw Banghua Zhu Stuart J. Russell Anca Dragan 41 2 0 13 Dec 2023
A safe exploration approach to constrained Markov decision processes Tingting Ni Maryam Kamgarpour 54 3 0 01 Dec 2023
Policy Optimization via Adv2: Adversarial Learning on Advantage Functions Matthieu Jonckheere Chiara Mignacco Gilles Stoltz 33 2 0 25 Oct 2023
When is Agnostic Reinforcement Learning Statistically Tractable? Zeyu Jia Gene Li Alexander Rakhlin Ayush Sekhari Nathan Srebro OffRL 37 5 0 09 Oct 2023
Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processes Qinbo Bai Washim Uddin Mondal Vaneet Aggarwal 34 9 0 05 Sep 2023
Settling the Sample Complexity of Online Reinforcement Learning Zihan Zhang Yuxin Chen Jason D. Lee S. Du OffRL 98 22 0 25 Jul 2023
Beyond Black-Box Advice: Learning-Augmented Algorithms for MDPs with Q-Value Predictions Tongxin Li Yiheng Lin Shaolei Ren Adam Wierman AAML OffRL 44 6 0 20 Jul 2023
Policy Finetuning in Reinforcement Learning via Design of Experiments using Offline Data Ruiqi Zhang Andrea Zanette OffRL OnRL 45 7 0 10 Jul 2023
Diverse Projection Ensembles for Distributional Reinforcement Learning Moritz A. Zanger Wendelin Bohmer M. Spaan 38 4 0 12 Jun 2023
Provably Efficient Adversarial Imitation Learning with Unknown Transitions Tian Xu Ziniu Li Yang Yu Zhimin Luo 18 8 0 11 Jun 2023
High-probability sample complexities for policy evaluation with linear function approximation Gen Li Weichen Wu Yuejie Chi Cong Ma Alessandro Rinaldo Yuting Wei OffRL 40 7 0 30 May 2023
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo Haque Ishfaq Qingfeng Lan Pan Xu A. R. Mahmood Doina Precup Anima Anandkumar Kamyar Azizzadenesheli BDL OffRL 33 20 0 29 May 2023
Zero-sum Polymatrix Markov Games: Equilibrium Collapse and Efficient Computation of Nash Equilibria Fivos Kalogiannis Ioannis Panageas 42 8 0 23 May 2023
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes Han Zhong Tong Zhang 40 26 0 15 May 2023
Bayesian Reinforcement Learning with Limited Cognitive Load Dilip Arumugam Mark K. Ho Noah D. Goodman Benjamin Van Roy OffRL 39 8 0 05 May 2023
Restarted Bayesian Online Change-point Detection for Non-Stationary Markov Decision Processes Réda Alami Mohammed Mahfoud Eric Moulines 24 2 0 01 Apr 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 49 18 0 14 Mar 2023
Wasserstein Actor-Critic: Directed Exploration via Optimism for Continuous-Actions Control Amarildo Likmeta Matteo Sacco Alberto Maria Metelli Marcello Restelli OffRL 28 3 0 04 Mar 2023
Provably Efficient Reinforcement Learning via Surprise Bound Hanlin Zhu Ruosong Wang Jason D. Lee OffRL 30 5 0 22 Feb 2023
Reinforcement Learning with Function Approximation: From Linear to Nonlinear Jihao Long Jiequn Han 39 5 0 20 Feb 2023
Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization Fang-yuan Kong Xiangcheng Zhang Baoxiang Wang Shuai Li 36 12 0 14 Feb 2023
Robust Knowledge Transfer in Tiered Reinforcement Learning Jiawei Huang Niao He OffRL 34 1 0 10 Feb 2023
Online Reinforcement Learning with Uncertain Episode Lengths Debmalya Mandal Goran Radanović Jiarui Gan Adish Singla R. Majumdar OffRL 38 5 0 07 Feb 2023
A Reduction-based Framework for Sequential Decision Making with Delayed Feedback Yunchang Yang Hangshi Zhong Tianhao Wu B. Liu Liwei Wang S. Du OffRL 32 8 0 03 Feb 2023
User-centric Heterogeneous-action Deep Reinforcement Learning for Virtual Reality in the Metaverse over Wireless Networks Wen-li Yu Terence Jie Chua Junfeng Zhao EgoV 45 18 0 03 Feb 2023
Sample Complexity of Kernel-Based Q-Learning Sing-Yuan Yeh Fu-Chieh Chang Chang-Wei Yueh Pei-Yuan Wu A. Bernacchia Sattar Vakili OffRL 35 4 0 01 Feb 2023
Learning in POMDPs is Sample-Efficient with Hindsight Observability Jonathan Lee Alekh Agarwal Christoph Dann Tong Zhang 39 20 0 31 Jan 2023