Sample Complexity Bounds for Two Timescale Value-based Reinforcement Learning Algorithms

10 November 2020

Papers citing "Sample Complexity Bounds for Two Timescale Value-based Reinforcement Learning Algorithms"

10 / 10 papers shown

Title
Regularized Q-Learning with Linear Function Approximation Jiachen Xi Alfredo Garcia P. Momcilovic 38 2 0 26 Jan 2024
Central Limit Theorem for Two-Timescale Stochastic Approximation with Markovian Noise: Theory and Applications Jie Hu Vishwaraj Doshi Do Young Eun 38 4 0 17 Jan 2024
Tight Finite Time Bounds of Two-Time-Scale Linear Stochastic Approximation with Markovian Noise Shaan ul Haque S. Khodadadian S. T. Maguluri 44 11 0 31 Dec 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 30 7 0 30 May 2023
Gauss-Newton Temporal Difference Learning with Nonlinear Function Approximation Zhifa Ke Junyu Zhang Zaiwen Wen 24 0 0 25 Feb 2023
Finite-Time Error Bounds for Greedy-GQ Yue Wang Yi Zhou Shaofeng Zou 34 1 0 06 Sep 2022
Target Network and Truncation Overcome The Deadly Triad in $Q$ -Learning Zaiwei Chen John-Paul Clarke S. T. Maguluri 23 19 0 05 Mar 2022
PER-ETD: A Polynomially Efficient Emphatic Temporal Difference Learning Method Ziwei Guan Tengyu Xu Yingbin Liang 15 4 0 13 Oct 2021
Online Robust Reinforcement Learning with Model Uncertainty Yue Wang Shaofeng Zou OOD OffRL 76 97 0 29 Sep 2021
Sample and Communication-Efficient Decentralized Actor-Critic Algorithms with Finite-Time Analysis Ziyi Chen Yi Zhou Rongrong Chen Shaofeng Zou 19 24 0 08 Sep 2021