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Online Target Q-learning with Reverse Experience Replay: Efficiently
  finding the Optimal Policy for Linear MDPs

Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs

16 October 2021
Naman Agarwal
Syomantak Chaudhuri
Prateek Jain
Dheeraj M. Nagaraj
Praneeth Netrapalli
    OffRL
ArXivPDFHTML

Papers citing "Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs"

12 / 12 papers shown
Title
Near-optimal Offline and Streaming Algorithms for Learning Non-Linear
  Dynamical Systems
Near-optimal Offline and Streaming Algorithms for Learning Non-Linear Dynamical Systems
Prateek Jain
S. Kowshik
Dheeraj M. Nagaraj
Praneeth Netrapalli
OffRL
30
23
0
24 May 2021
Streaming Linear System Identification with Reverse Experience Replay
Streaming Linear System Identification with Reverse Experience Replay
Prateek Jain
S. Kowshik
Dheeraj M. Nagaraj
Praneeth Netrapalli
OffRL
50
19
0
10 Mar 2021
Momentum Q-learning with Finite-Sample Convergence Guarantee
Momentum Q-learning with Finite-Sample Convergence Guarantee
Bowen Weng
Huaqing Xiong
Linna Zhao
Yingbin Liang
Wei Zhang
43
8
0
30 Jul 2020
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning
  with a Generative Model
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model
Gen Li
Yuting Wei
Yuejie Chi
Yuxin Chen
91
128
0
26 May 2020
Finite-Time Analysis of Asynchronous Stochastic Approximation and
  $Q$-Learning
Finite-Time Analysis of Asynchronous Stochastic Approximation and QQQ-Learning
Guannan Qu
Adam Wierman
50
110
0
01 Feb 2020
Finite-Time Performance Bounds and Adaptive Learning Rate Selection for
  Two Time-Scale Reinforcement Learning
Finite-Time Performance Bounds and Adaptive Learning Rate Selection for Two Time-Scale Reinforcement Learning
Harsh Gupta
R. Srikant
Lei Ying
54
86
0
14 Jul 2019
Provably Efficient Reinforcement Learning with Linear Function
  Approximation
Provably Efficient Reinforcement Learning with Linear Function Approximation
Chi Jin
Zhuoran Yang
Zhaoran Wang
Michael I. Jordan
86
555
0
11 Jul 2019
Model-Based Reinforcement Learning with a Generative Model is Minimax
  Optimal
Model-Based Reinforcement Learning with a Generative Model is Minimax Optimal
Alekh Agarwal
Sham Kakade
Lin F. Yang
OffRL
81
170
0
10 Jun 2019
Finite-Sample Analysis of Nonlinear Stochastic Approximation with
  Applications in Reinforcement Learning
Finite-Sample Analysis of Nonlinear Stochastic Approximation with Applications in Reinforcement Learning
Zaiwei Chen
Sheng Zhang
Thinh T. Doan
John-Paul Clarke
S. T. Maguluri
55
59
0
27 May 2019
Stochastic approximation with cone-contractive operators: Sharp
  $\ell_\infty$-bounds for $Q$-learning
Stochastic approximation with cone-contractive operators: Sharp ℓ∞\ell_\inftyℓ∞​-bounds for QQQ-learning
Martin J. Wainwright
43
105
0
15 May 2019
Finite-Time Error Bounds For Linear Stochastic Approximation and TD
  Learning
Finite-Time Error Bounds For Linear Stochastic Approximation and TD Learning
R. Srikant
Lei Ying
63
252
0
03 Feb 2019
A Finite Time Analysis of Temporal Difference Learning With Linear
  Function Approximation
A Finite Time Analysis of Temporal Difference Learning With Linear Function Approximation
Jalaj Bhandari
Daniel Russo
Raghav Singal
101
339
0
06 Jun 2018
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