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Provably Efficient Reinforcement Learning with Linear Function Approximation

11 July 2019

Papers citing "Provably Efficient Reinforcement Learning with Linear Function Approximation"

50 / 417 papers shown

Title
Augmenting Online RL with Offline Data is All You Need: A Unified Hybrid RL Algorithm Design and Analysis Ruiquan Huang Donghao Li Chengshuai Shi Cong Shen Jing Yang OffRL 112 0 0 01 Jul 2025
Learning Task-Agnostic Skill Bases to Uncover Motor Primitives in Animal Behaviors Jiyi Wang Jingyang Ke Bo Dai Anqi Wu 17 0 0 18 Jun 2025
The Sample Complexity of Online Strategic Decision Making with Information Asymmetry and Knowledge Transportability Jiachen Hu Rui Ai Han Zhong Xiaoyu Chen L. Wang Zhaoran Wang Zhuoran Yang 67 0 0 11 Jun 2025
MOBODY: Model Based Off-Dynamics Offline Reinforcement Learning Yihong Guo Yu Yang Pan Xu Anqi Liu OffRL 47 0 0 10 Jun 2025
From Debate to Equilibrium: Belief-Driven Multi-Agent LLM Reasoning via Bayesian Nash Equilibrium Xie Yi Zhanke Zhou Chentao Cao Qiyu Niu Tongliang Liu Bo Han 27 0 0 09 Jun 2025
Provable Reinforcement Learning from Human Feedback with an Unknown Link Function Qining Zhang Lei Ying 75 0 0 03 Jun 2025
Generalized Linear Markov Decision Process Sinian Zhang Kaicheng Zhang Ziping Xu Tianxi Cai D. Zhou 54 0 0 01 Jun 2025
Universal Value-Function Uncertainties Moritz A. Zanger Max Weltevrede Yaniv Oren Pascal R. van der Vaart Caroline Horsch Wendelin Bohmer M. Spaan OffRL 79 0 0 27 May 2025
Towards Optimal Differentially Private Regret Bounds in Linear MDPs Sharan Sahu 124 0 0 12 Apr 2025
CAE: Repurposing the Critic as an Explorer in Deep Reinforcement Learning Yexin Li Pring Wong Hanfang Zhang Shuo Chen Siyuan Qi OffRL 87 1 0 23 Mar 2025
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model Moritz A. Zanger Pascal R. van der Vaart Wendelin Bohmer M. Spaan UQCV BDL 518 2 0 14 Mar 2025
Quantum Non-Linear Bandit Optimization Zakaria Shams Siam Chaowen Guan Chong Liu 91 0 0 04 Mar 2025
Minimax Optimal Reinforcement Learning with Quasi-Optimism Harin Lee Min-hwan Oh OffRL 105 1 0 02 Mar 2025
Towards Understanding the Benefit of Multitask Representation Learning in Decision Process Rui Lu Yang Yue Andrew Zhao S. Du Gao Huang OffRL 101 1 0 01 Mar 2025
Provably Efficient RL for Linear MDPs under Instantaneous Safety Constraints in Non-Convex Feature Spaces Amirhossein Roknilamouki A. Ghosh Ming Shi Fatemeh Nourzad Eylem Ekici Ness B. Shroff 95 0 0 25 Feb 2025
Stochastic Semi-Gradient Descent for Learning Mean Field Games with Population-Aware Function Approximation Chenyu Zhang Xu Chen Xuan Di 148 5 0 17 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 140 2 0 13 Feb 2025
Towards General-Purpose Model-Free Reinforcement Learning Scott Fujimoto P. DÓro Amy Zhang Yuandong Tian Michael Rabbat OffRL 107 6 0 28 Jan 2025
Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation Long-Fei Li Yu Zhang Peng Zhao Zhi Zhou 255 5 0 17 Jan 2025
Digital Twin Calibration with Model-Based Reinforcement Learning Hua Zheng Wei Xie I. Ryzhov Keilung Choy 115 0 0 04 Jan 2025
Hybrid Preference Optimization for Alignment: Provably Faster Convergence Rates by Combining Offline Preferences with Online Exploration Avinandan Bose Zhihan Xiong Aadirupa Saha S. Du Maryam Fazel 123 1 0 13 Dec 2024
Mean-Field Sampling for Cooperative Multi-Agent Reinforcement Learning Emile Anand Ishani Karmarkar Guannan Qu 179 2 0 01 Dec 2024
On the Linear Speedup of Personalized Federated Reinforcement Learning with Shared Representations Guojun Xiong Shufan Wang Daniel Jiang Jian Li FedML 153 1 0 22 Nov 2024
Efficient, Low-Regret, Online Reinforcement Learning for Linear MDPs Philips George John Arnab Bhattacharyya Silviu Maniu Dimitrios Myrisiotis Zhenan Wu OffRL 85 0 0 16 Nov 2024
Near-Optimal Dynamic Regret for Adversarial Linear Mixture MDPs Long-Fei Li Peng Zhao Zhi Zhou 81 1 0 05 Nov 2024
Provably and Practically Efficient Adversarial Imitation Learning with General Function Approximation Tian Xu Zhilong Zhang Ruishuo Chen Yihao Sun Yang Yu 88 1 0 01 Nov 2024
Demystifying Linear MDPs and Novel Dynamics Aggregation Framework Joongkyu Lee Min-hwan Oh 67 2 0 31 Oct 2024
Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs Davide Maran Alberto Maria Metelli Matteo Papini Marcello Restelli 98 0 0 31 Oct 2024
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 470 1 0 31 Oct 2024
Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm Sattar Vakili Julia Olkhovskaya 60 0 0 30 Oct 2024
NetworkGym: Reinforcement Learning Environments for Multi-Access Traffic Management in Network Simulation Momin Haider Ming Yin Menglei Zhang Arpit Gupta Jing Zhu Yu-Xiang Wang OffRL 64 1 0 30 Oct 2024
Primal-Dual Spectral Representation for Off-policy Evaluation Yang Hu Tianyi Chen Na Li Kai Wang Bo Dai OffRL 87 0 0 23 Oct 2024
Scalable spectral representations for multi-agent reinforcement learning in network MDPs Tongzheng Ren Runyu Zhang Bo Dai 99 0 0 22 Oct 2024
Learning Infinite-Horizon Average-Reward Linear Mixture MDPs of Bounded Span Woojin Chae Kihyuk Hong Yufan Zhang Ambuj Tewari Dabeen Lee 69 1 0 19 Oct 2024
Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples Thomas T. Zhang Bruce D. Lee Ingvar M. Ziemann George J. Pappas Nikolai Matni CML OOD 145 0 0 15 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 90 3 0 11 Oct 2024
Corruption-Robust Linear Bandits: Minimax Optimality and Gap-Dependent Misspecification Haolin Liu Artin Tajdini Andrew Wagenmaker Chen-Yu Wei 75 1 0 10 Oct 2024
DOPL: Direct Online Preference Learning for Restless Bandits with Preference Feedback Guojun Xiong Ujwal Dinesha Debajoy Mukherjee Jian Li Srinivas Shakkottai 75 2 0 07 Oct 2024
Task Diversity Shortens the ICL Plateau Jaeyeon Kim Sehyun Kwon Joo Young Choi Jongho Park Jaewoong Cho Jason D. Lee Ernest K. Ryu MoMe 101 3 0 07 Oct 2024
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling Jasmine Bayrooti Carl Henrik Ek Amanda Prorok 199 0 0 07 Oct 2024
Upper and Lower Bounds for Distributionally Robust Off-Dynamics Reinforcement Learning Zhishuai Liu Weixin Wang Pan Xu 103 5 0 30 Sep 2024
Hybrid Reinforcement Learning Breaks Sample Size Barriers in Linear MDPs Kevin Tan Wei Fan Yuting Wei OffRL 110 3 0 08 Aug 2024
Misspecified $Q$ -Learning with Sparse Linear Function Approximation: Tight Bounds on Approximation Error Ally Yalei Du Lin F. Yang Ruosong Wang 71 0 0 18 Jul 2024
Random Latent Exploration for Deep Reinforcement Learning Srinath Mahankali Zhang-Wei Hong Ayush Sekhari Alexander Rakhlin Pulkit Agrawal 264 3 0 18 Jul 2024
Satisficing Exploration for Deep Reinforcement Learning Dilip Arumugam Saurabh Kumar Ramki Gummadi Benjamin Van Roy 67 1 0 16 Jul 2024
BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning Hao-ming Lin Wenhao Ding Jian Chen Laixi Shi Jiacheng Zhu Yue Liu Ding Zhao OffRL CML 131 0 0 15 Jul 2024
Spectral Representation for Causal Estimation with Hidden Confounders Zhaolin Ren Haotian Sun Antoine Moulin Arthur Gretton Bo Dai CML 130 3 0 15 Jul 2024
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning Dake Zhang Boxiang Lyu Shuang Qiu Mladen Kolar Tong Zhang OffRL 80 0 0 10 Jul 2024
When does Self-Prediction help? Understanding Auxiliary Tasks in Reinforcement Learning C. Voelcker Tyler Kastner Igor Gilitschenski Amir-massoud Farahmand SSL 93 6 0 25 Jun 2024
Uncertainty-Aware Reward-Free Exploration with General Function Approximation Junkai Zhang Weitong Zhang Dongruo Zhou Q. Gu 108 3 0 24 Jun 2024