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Gradient Temporal-Difference Learning with Regularized Corrections

Gradient Temporal-Difference Learning with Regularized Corrections

1 July 2020
Sina Ghiassian
Andrew Patterson
Shivam Garg
Dhawal Gupta
Adam White
Martha White
ArXivPDFHTML

Papers citing "Gradient Temporal-Difference Learning with Regularized Corrections"

14 / 14 papers shown
Title
Central Limit Theorem for Two-Timescale Stochastic Approximation with
  Markovian Noise: Theory and Applications
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
Gauss-Newton Temporal Difference Learning with Nonlinear Function
  Approximation
Gauss-Newton Temporal Difference Learning with Nonlinear Function Approximation
Zhifa Ke
Junyu Zhang
Zaiwen Wen
24
0
0
25 Feb 2023
Why Target Networks Stabilise Temporal Difference Methods
Why Target Networks Stabilise Temporal Difference Methods
Matt Fellows
Matthew Smith
Shimon Whiteson
OOD
AAML
21
7
0
24 Feb 2023
Backstepping Temporal Difference Learning
Backstepping Temporal Difference Learning
Han-Dong Lim
Dong-hwan Lee
OffRL
33
2
0
20 Feb 2023
Bridging the Gap Between Target Networks and Functional Regularization
Alexandre Piché
Valentin Thomas
Joseph Marino
Rafael Pardiñas
Gian Maria Marconi
C. Pal
Mohammad Emtiyaz Khan
14
1
0
21 Oct 2022
Gradient Descent Temporal Difference-difference Learning
Gradient Descent Temporal Difference-difference Learning
Rong Zhu
James M. Murray
OffRL
19
1
0
10 Sep 2022
Robust Losses for Learning Value Functions
Robust Losses for Learning Value Functions
Andrew Patterson
Victor Liao
Martha White
28
12
0
17 May 2022
Regularized Q-learning
Regularized Q-learning
Han-Dong Lim
Donghwan Lee
27
10
0
11 Feb 2022
A Temporal-Difference Approach to Policy Gradient Estimation
A Temporal-Difference Approach to Policy Gradient Estimation
Samuele Tosatto
Andrew Patterson
Martha White
A. R. Mahmood
OffRL
27
1
0
04 Feb 2022
New Versions of Gradient Temporal Difference Learning
New Versions of Gradient Temporal Difference Learning
Dong-hwan Lee
Han-Dong Lim
Jihoon Park
Okyong Choi
42
5
0
09 Sep 2021
Convergent and Efficient Deep Q Network Algorithm
Convergent and Efficient Deep Q Network Algorithm
Zhikang T. Wang
Masahito Ueda
27
12
0
29 Jun 2021
An Empirical Comparison of Off-policy Prediction Learning Algorithms on
  the Collision Task
An Empirical Comparison of Off-policy Prediction Learning Algorithms on the Collision Task
Sina Ghiassian
R. Sutton
AAML
OffRL
19
5
0
02 Jun 2021
Revisiting Rainbow: Promoting more Insightful and Inclusive Deep
  Reinforcement Learning Research
Revisiting Rainbow: Promoting more Insightful and Inclusive Deep Reinforcement Learning Research
J. Obando-Ceron
Pablo Samuel Castro
OffRL
20
105
0
20 Nov 2020
Affordance as general value function: A computational model
Affordance as general value function: A computational model
D. Graves
Johannes Günther
Jun Luo
AI4CE
21
6
0
27 Oct 2020
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