ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2203.02628
  4. Cited By
Target Network and Truncation Overcome The Deadly Triad in $Q$-Learning
v1v2 (latest)

Target Network and Truncation Overcome The Deadly Triad in QQQ-Learning

5 March 2022
Zaiwei Chen
John-Paul Clarke
S. T. Maguluri
ArXiv (abs)PDFHTML

Papers citing "Target Network and Truncation Overcome The Deadly Triad in $Q$-Learning"

15 / 15 papers shown
Title
Understanding the theoretical properties of projected Bellman equation, linear Q-learning, and approximate value iteration
Understanding the theoretical properties of projected Bellman equation, linear Q-learning, and approximate value iteration
Han-Dong Lim
Donghwan Lee
58
0
0
15 Apr 2025
Dual Approximation Policy Optimization
Dual Approximation Policy Optimization
Zhihan Xiong
Maryam Fazel
Lin Xiao
72
1
0
02 Oct 2024
Improving Deep Reinforcement Learning by Reducing the Chain Effect of
  Value and Policy Churn
Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn
Hongyao Tang
Glen Berseth
OffRL
97
2
0
07 Sep 2024
Target Networks and Over-parameterization Stabilize Off-policy
  Bootstrapping with Function Approximation
Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation
Fengdi Che
Chenjun Xiao
Jincheng Mei
Bo Dai
Ramki Gummadi
Oscar A Ramirez
Christopher K Harris
A. R. Mahmood
Dale Schuurmans
78
5
0
31 May 2024
Enhancing Q-Learning with Large Language Model Heuristics
Enhancing Q-Learning with Large Language Model Heuristics
Xiefeng Wu
LRM
100
0
0
06 May 2024
Analysis of Off-Policy Multi-Step TD-Learning with Linear Function
  Approximation
Analysis of Off-Policy Multi-Step TD-Learning with Linear Function Approximation
Donghwan Lee
86
0
0
24 Feb 2024
Regularized Q-Learning with Linear Function Approximation
Regularized Q-Learning with Linear Function Approximation
Jiachen Xi
Alfredo Garcia
P. Momcilovic
120
2
0
26 Jan 2024
Multi-Bellman operator for convergence of $Q$-learning with linear
  function approximation
Multi-Bellman operator for convergence of QQQ-learning with linear function approximation
Diogo S. Carvalho
D. L. McPherson
Francisco S. Melo
62
1
0
28 Sep 2023
Stability of Q-Learning Through Design and Optimism
Stability of Q-Learning Through Design and Optimism
Sean P. Meyn
91
10
0
05 Jul 2023
Performance Bounds for Policy-Based Average Reward Reinforcement
  Learning Algorithms
Performance Bounds for Policy-Based Average Reward Reinforcement Learning Algorithms
Yashaswini Murthy
Mehrdad Moharrami
R. Srikant
OffRL
70
5
0
02 Feb 2023
Finite time analysis of temporal difference learning with linear
  function approximation: Tail averaging and regularisation
Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularisation
Gandharv Patil
Prashanth L.A.
Dheeraj M. Nagaraj
Doina Precup
84
15
0
12 Oct 2022
A Note on Target Q-learning For Solving Finite MDPs with A Generative
  Oracle
A Note on Target Q-learning For Solving Finite MDPs with A Generative Oracle
Ziniu Li
Tian Xu
Yang Yu
90
5
0
22 Mar 2022
The Efficacy of Pessimism in Asynchronous Q-Learning
The Efficacy of Pessimism in Asynchronous Q-Learning
Yuling Yan
Gen Li
Yuxin Chen
Jianqing Fan
OffRL
159
41
0
14 Mar 2022
Regularized Q-learning
Regularized Q-learning
Han-Dong Lim
Donghwan Lee
102
11
0
11 Feb 2022
Rethinking ValueDice: Does It Really Improve Performance?
Rethinking ValueDice: Does It Really Improve Performance?
Ziniu Li
Tian Xu
Yang Yu
Zhimin Luo
OffRL
79
17
0
05 Feb 2022
1