Improved Regret Bounds for Linear Adversarial MDPs via Linear
Optimization

Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization

14 February 2023

Xiangcheng Zhang

Baoxiang Wang

Shuai Li

Papers citing "Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization"

9 / 9 papers shown

Title
Decision Making in Hybrid Environments: A Model Aggregation Approach Haolin Liu Chen-Yu Wei Julian Zimmert 86 0 0 09 Feb 2025
Refined Sample Complexity for Markov Games with Independent Linear Function Approximation Yan Dai Qiwen Cui S. S. Du 41 1 0 11 Feb 2024
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes Han Zhong Tong Zhang 32 26 0 15 May 2023
Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation Uri Sherman Tomer Koren Yishay Mansour 32 12 0 30 Jan 2023
Refined Regret for Adversarial MDPs with Linear Function Approximation Yan Dai Haipeng Luo Chen-Yu Wei Julian Zimmert 23 12 0 30 Jan 2023
Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs Naman Agarwal Syomantak Chaudhuri Prateek Jain Dheeraj M. Nagaraj Praneeth Netrapalli OffRL 38 21 0 16 Oct 2021
Near-optimal Policy Optimization Algorithms for Learning Adversarial Linear Mixture MDPs Jiafan He Dongruo Zhou Quanquan Gu 95 23 0 17 Feb 2021
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints Chi Jin Zhuoran Yang Zhaoran Wang OffRL 122 166 0 06 Jan 2021
Deep Reinforcement Learning for Autonomous Driving: A Survey B. R. Kiran Ibrahim Sobh V. Talpaert Patrick Mannion A. A. Sallab S. Yogamani P. Pérez 165 1,632 0 02 Feb 2020