A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes

15 May 2023

Tong Zhang

Papers citing "A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes"

22 / 22 papers shown

Title
Enhancing PPO with Trajectory-Aware Hybrid Policies Qisai Liu Zhanhong Jiang Hsin-Jung Yang Mahsa Khosravi Joshua R. Waite S. Sarkar 44 0 0 21 Feb 2025
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning Dake Zhang Boxiang Lyu Shuang Qiu Mladen Kolar Tong Zhang OffRL 30 0 0 10 Jul 2024
Narrowing the Gap between Adversarial and Stochastic MDPs via Policy Optimization D. Tiapkin Evgenii Chzhen Gilles Stoltz 74 0 0 08 Jul 2024
Warm-up Free Policy Optimization: Improved Regret in Linear Markov Decision Processes Asaf B. Cassel Aviv A. Rosenberg 35 1 0 03 Jul 2024
Imitation Learning in Discounted Linear MDPs without exploration assumptions Luca Viano Stratis Skoulakis V. Cevher 30 3 0 03 May 2024
DPO Meets PPO: Reinforced Token Optimization for RLHF Han Zhong Guhao Feng Guhao Feng Li Zhao Di He Jiang Bian Liwei Wang Jiang Bian Liwei Wang 55 56 0 29 Apr 2024
Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation Jianliang He Han Zhong Zhuoran Yang 26 6 0 19 Apr 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 71 4 0 04 Apr 2024
Improved Algorithm for Adversarial Linear Mixture MDPs with Bandit Feedback and Unknown Transition Long-Fei Li Peng Zhao Zhi-Hua Zhou 42 4 0 07 Mar 2024
Rethinking Model-based, Policy-based, and Value-based Reinforcement Learning via the Lens of Representation Complexity Guhao Feng Han Zhong OffRL 68 3 0 28 Dec 2023
Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-Constraint Wei Xiong Hanze Dong Chen Ye Ziqi Wang Han Zhong Heng Ji Nan Jiang Tong Zhang OffRL 36 155 0 18 Dec 2023
Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback Canzhe Zhao Ruofeng Yang Baoxiang Wang Xuezhou Zhang Shuai Li 22 2 0 14 Nov 2023
Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback Haolin Liu Chen-Yu Wei Julian Zimmert 22 6 0 17 Oct 2023
Rate-Optimal Policy Optimization for Linear Markov Decision Processes Uri Sherman Alon Cohen Tomer Koren Yishay Mansour 33 7 0 28 Aug 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 22 6 0 12 Jun 2023
Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration Zhihan Liu Miao Lu Wei Xiong Han Zhong Haotian Hu Shenao Zhang Sirui Zheng Zhuoran Yang Zhaoran Wang OffRL 32 22 0 29 May 2023
Computationally Efficient Horizon-Free Reinforcement Learning for Linear Mixture MDPs Dongruo Zhou Quanquan Gu 73 43 0 23 May 2022
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 303 11,909 0 04 Mar 2022
First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach Andrew Wagenmaker Yifang Chen Max Simchowitz S. Du Kevin G. Jamieson 71 36 0 07 Dec 2021
Near-optimal Policy Optimization Algorithms for Learning Adversarial Linear Mixture MDPs Jiafan He Dongruo Zhou Quanquan Gu 95 23 0 17 Feb 2021
Improved Variance-Aware Confidence Sets for Linear Bandits and Linear Mixture MDP Zihan Zhang Jiaqi Yang Xiangyang Ji S. Du 59 36 0 29 Jan 2021
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints Chi Jin Zhuoran Yang Zhaoran Wang OffRL 107 166 0 06 Jan 2021