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

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

15 May 2023

Tong Zhang

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

8 / 8 papers shown

Title
Enhancing PPO with Trajectory-Aware Hybrid Policies Qisai Liu Zhanhong Jiang Hsin-Jung Yang Mahsa Khosravi Joshua R. Waite Soumik Sarkar 112 0 0 21 Feb 2025
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning Dake Zhang Boxiang Lyu Shuang Qiu Mladen Kolar Tong Zhang OffRL 78 0 0 10 Jul 2024
Narrowing the Gap between Adversarial and Stochastic MDPs via Policy Optimization D. Tiapkin Evgenii Chzhen Gilles Stoltz 125 1 0 08 Jul 2024
DPO Meets PPO: Reinforced Token Optimization for RLHF Han Zhong Zikang Shan Guhao Feng Wei Xiong Xinle Cheng Li Zhao Di He Jiang Bian Liwei Wang 155 72 0 29 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 107 10 0 04 Apr 2024
Improved Algorithm for Adversarial Linear Mixture MDPs with Bandit Feedback and Unknown Transition Long-Fei Li Peng Zhao Zhi Zhou 88 6 0 07 Mar 2024
Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback Haolin Liu Chen-Yu Wei Julian Zimmert 78 6 0 17 Oct 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 83 10 0 12 Jun 2023

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