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Deep Reinforcement Learning and the Deadly Triad

Deep Reinforcement Learning and the Deadly Triad

6 December 2018
H. V. Hasselt
Yotam Doron
Florian Strub
Matteo Hessel
Nicolas Sonnerat
Joseph Modayil
    OffRL
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Papers citing "Deep Reinforcement Learning and the Deadly Triad"

50 / 51 papers shown
Title
Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets
Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets
Zhen Liu
Tim Z. Xiao
Weiyang Liu
Yoshua Bengio
Dinghuai Zhang
123
2
0
10 Dec 2024
DIAR: Diffusion-model-guided Implicit Q-learning with Adaptive
  Revaluation
DIAR: Diffusion-model-guided Implicit Q-learning with Adaptive Revaluation
Jaehyun Park
Yunho Kim
Sejin Kim
Byung-Jun Lee
Sundong Kim
OffRL
30
1
0
15 Oct 2024
Frequency and Generalisation of Periodic Activation Functions in Reinforcement Learning
Frequency and Generalisation of Periodic Activation Functions in Reinforcement Learning
Augustine N. Mavor-Parker
Matthew J. Sargent
Caswell Barry
Lewis D. Griffin
Clare Lyle
47
2
0
09 Jul 2024
Simplifying Deep Temporal Difference Learning
Simplifying Deep Temporal Difference Learning
Matteo Gallici
Mattie Fellows
Benjamin Ellis
B. Pou
Ivan Masmitja
Jakob Foerster
Mario Martin
OffRL
62
15
0
05 Jul 2024
Is Value Functions Estimation with Classification Plug-and-play for
  Offline Reinforcement Learning?
Is Value Functions Estimation with Classification Plug-and-play for Offline Reinforcement Learning?
Denis Tarasov
Kirill Brilliantov
Dmitrii Kharlapenko
OffRL
32
2
0
10 Jun 2024
Multi-agent Reinforcement Learning: A Comprehensive Survey
Multi-agent Reinforcement Learning: A Comprehensive Survey
Dom Huh
Prasant Mohapatra
AI4CE
33
8
0
15 Dec 2023
Adaptive Ensemble Q-learning: Minimizing Estimation Bias via Error
  Feedback
Adaptive Ensemble Q-learning: Minimizing Estimation Bias via Error Feedback
Hang Wang
Sen Lin
Junshan Zhang
19
19
0
20 Jun 2023
Diverse Projection Ensembles for Distributional Reinforcement Learning
Diverse Projection Ensembles for Distributional Reinforcement Learning
Moritz A. Zanger
Wendelin Bohmer
M. Spaan
25
4
0
12 Jun 2023
Distance Weighted Supervised Learning for Offline Interaction Data
Distance Weighted Supervised Learning for Offline Interaction Data
Joey Hejna
Jensen Gao
Dorsa Sadigh
OffRL
36
12
0
26 Apr 2023
The Dormant Neuron Phenomenon in Deep Reinforcement Learning
The Dormant Neuron Phenomenon in Deep Reinforcement Learning
Ghada Sokar
Rishabh Agarwal
Pablo Samuel Castro
Utku Evci
CLL
51
88
0
24 Feb 2023
Learning to Optimize for Reinforcement Learning
Learning to Optimize for Reinforcement Learning
Qingfeng Lan
Rupam Mahmood
Shuicheng Yan
Zhongwen Xu
OffRL
26
6
0
03 Feb 2023
Distillation Policy Optimization
Distillation Policy Optimization
Jianfei Ma
OffRL
21
1
0
01 Feb 2023
SoK: Adversarial Machine Learning Attacks and Defences in Multi-Agent
  Reinforcement Learning
SoK: Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learning
Maxwell Standen
Junae Kim
Claudia Szabo
AAML
29
5
0
11 Jan 2023
A Survey on Transformers in Reinforcement Learning
A Survey on Transformers in Reinforcement Learning
Wenzhe Li
Hao Luo
Zichuan Lin
Chongjie Zhang
Zongqing Lu
Deheng Ye
OffRL
MU
AI4CE
37
55
0
08 Jan 2023
Is Conditional Generative Modeling all you need for Decision-Making?
Is Conditional Generative Modeling all you need for Decision-Making?
Anurag Ajay
Yilun Du
Abhi Gupta
J. Tenenbaum
Tommi Jaakkola
Pulkit Agrawal
DiffM
47
360
0
28 Nov 2022
Adversarial Cheap Talk
Adversarial Cheap Talk
Chris Xiaoxuan Lu
Timon Willi
Alistair Letcher
Jakob N. Foerster
AAML
24
17
0
20 Nov 2022
Control Transformer: Robot Navigation in Unknown Environments through
  PRM-Guided Return-Conditioned Sequence Modeling
Control Transformer: Robot Navigation in Unknown Environments through PRM-Guided Return-Conditioned Sequence Modeling
Daniel Lawson
A. H. Qureshi
24
7
0
11 Nov 2022
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
A Policy-Guided Imitation Approach for Offline Reinforcement Learning
A Policy-Guided Imitation Approach for Offline Reinforcement Learning
Haoran Xu
Li Jiang
Jianxiong Li
Xianyuan Zhan
OffRL
26
61
0
15 Oct 2022
Factors of Influence of the Overestimation Bias of Q-Learning
Factors of Influence of the Overestimation Bias of Q-Learning
Julius Wagenbach
M. Sabatelli
15
1
0
11 Oct 2022
Reducing Variance in Temporal-Difference Value Estimation via Ensemble
  of Deep Networks
Reducing Variance in Temporal-Difference Value Estimation via Ensemble of Deep Networks
Litian Liang
Yaosheng Xu
Stephen Marcus McAleer
Dailin Hu
Alexander Ihler
Pieter Abbeel
Roy Fox
OOD
19
16
0
16 Sep 2022
Improved Policy Optimization for Online Imitation Learning
Improved Policy Optimization for Online Imitation Learning
J. Lavington
Sharan Vaswani
Mark W. Schmidt
OffRL
18
6
0
29 Jul 2022
Multi-objective Optimization of Notifications Using Offline
  Reinforcement Learning
Multi-objective Optimization of Notifications Using Offline Reinforcement Learning
Prakruthi Prabhakar
Yiping Yuan
Guangyu Yang
Wensheng Sun
A. Muralidharan
OffRL
28
6
0
07 Jul 2022
Stabilizing Off-Policy Deep Reinforcement Learning from Pixels
Stabilizing Off-Policy Deep Reinforcement Learning from Pixels
Edoardo Cetin
Philip J. Ball
Steve Roberts
Oya Celiktutan
30
36
0
03 Jul 2022
Critic Sequential Monte Carlo
Critic Sequential Monte Carlo
Vasileios Lioutas
J. Lavington
Justice Sefas
Matthew Niedoba
Yunpeng Liu
Berend Zwartsenberg
Setareh Dabiri
Frank D. Wood
Adam Scibior
44
7
0
30 May 2022
Robust Losses for Learning Value Functions
Robust Losses for Learning Value Functions
Andrew Patterson
Victor Liao
Martha White
23
12
0
17 May 2022
deep-significance - Easy and Meaningful Statistical Significance Testing
  in the Age of Neural Networks
deep-significance - Easy and Meaningful Statistical Significance Testing in the Age of Neural Networks
Dennis Ulmer
Christian Hardmeier
J. Frellsen
48
42
0
14 Apr 2022
Bayesian Structure Learning with Generative Flow Networks
Bayesian Structure Learning with Generative Flow Networks
T. Deleu
António Góis
Chris C. Emezue
M. Rankawat
Simon Lacoste-Julien
Stefan Bauer
Yoshua Bengio
BDL
48
143
0
28 Feb 2022
Using Deep Reinforcement Learning with Automatic Curriculum Learning for
  Mapless Navigation in Intralogistics
Using Deep Reinforcement Learning with Automatic Curriculum Learning for Mapless Navigation in Intralogistics
Honghu Xue
Benedikt Hein
M. Bakr
Georg Schildbach
Bengt Abel
Elmar Rueckert
16
15
0
23 Feb 2022
Selective Credit Assignment
Selective Credit Assignment
Veronica Chelu
Diana Borsa
Doina Precup
Hado van Hasselt
24
2
0
20 Feb 2022
Uncovering Instabilities in Variational-Quantum Deep Q-Networks
Uncovering Instabilities in Variational-Quantum Deep Q-Networks
Maja Franz
Lucas Wolf
Maniraman Periyasamy
Christian Ufrecht
Daniel D. Scherer
Axel Plinge
Christopher Mutschler
Wolfgang Mauerer
26
29
0
10 Feb 2022
Offline Reinforcement Learning for Mobile Notifications
Offline Reinforcement Learning for Mobile Notifications
Yiping Yuan
A. Muralidharan
Preetam Nandy
Miao Cheng
Prakruthi Prabhakar
OffRL
20
9
0
04 Feb 2022
Deep Q-learning: a robust control approach
Deep Q-learning: a robust control approach
B. Varga
Balázs Kulcsár
M. Chehreghani
OOD
22
9
0
21 Jan 2022
Chaining Value Functions for Off-Policy Learning
Chaining Value Functions for Off-Policy Learning
Simon Schmitt
John Shawe-Taylor
Hado van Hasselt
OffRL
23
2
0
17 Jan 2022
DR3: Value-Based Deep Reinforcement Learning Requires Explicit
  Regularization
DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization
Aviral Kumar
Rishabh Agarwal
Tengyu Ma
Aaron Courville
George Tucker
Sergey Levine
OffRL
31
65
0
09 Dec 2021
The Impact of Data Distribution on Q-learning with Function
  Approximation
The Impact of Data Distribution on Q-learning with Function Approximation
Pedro P. Santos
Diogo S. Carvalho
A. Sardinha
Francisco S. Melo
OffRL
11
2
0
23 Nov 2021
Hybrid BYOL-ViT: Efficient approach to deal with small datasets
Hybrid BYOL-ViT: Efficient approach to deal with small datasets
Safwen Naimi
Rien van Leeuwen
W. Souidène
S. B. Saoud
SSL
ViT
25
2
0
08 Nov 2021
Off-Policy Correction for Deep Deterministic Policy Gradient Algorithms
  via Batch Prioritized Experience Replay
Off-Policy Correction for Deep Deterministic Policy Gradient Algorithms via Batch Prioritized Experience Replay
Dogan C. Cicek
Enes Duran
Baturay Saglam
Furkan B. Mutlu
Suleyman Serdar Kozat
OffRL
11
11
0
02 Nov 2021
On the Estimation Bias in Double Q-Learning
On the Estimation Bias in Double Q-Learning
Zhizhou Ren
Guangxiang Zhu
Haotian Hu
Beining Han
Jian-Hai Chen
Chongjie Zhang
16
17
0
29 Sep 2021
Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework
  and Survey
Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework and Survey
Richard Dazeley
Peter Vamplew
Francisco Cruz
32
59
0
20 Aug 2021
Convergent and Efficient Deep Q Network Algorithm
Convergent and Efficient Deep Q Network Algorithm
Zhikang T. Wang
Masahito Ueda
14
12
0
29 Jun 2021
Modularity in Reinforcement Learning via Algorithmic Independence in
  Credit Assignment
Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment
Michael Chang
Sid Kaushik
Sergey Levine
Thomas L. Griffiths
28
8
0
28 Jun 2021
Single and Multi-Agent Deep Reinforcement Learning for AI-Enabled
  Wireless Networks: A Tutorial
Single and Multi-Agent Deep Reinforcement Learning for AI-Enabled Wireless Networks: A Tutorial
Amal Feriani
E. Hossain
35
236
0
06 Nov 2020
GRAC: Self-Guided and Self-Regularized Actor-Critic
GRAC: Self-Guided and Self-Regularized Actor-Critic
Lin Shao
Yifan You
Mengyuan Yan
Qingyun Sun
Jeannette Bohg
16
23
0
18 Sep 2020
A Unifying Framework for Reinforcement Learning and Planning
A Unifying Framework for Reinforcement Learning and Planning
Thomas M. Moerland
Joost Broekens
Aske Plaat
Catholijn M. Jonker
OffRL
27
9
0
26 Jun 2020
Bootstrap your own latent: A new approach to self-supervised Learning
Bootstrap your own latent: A new approach to self-supervised Learning
Jean-Bastien Grill
Florian Strub
Florent Altché
Corentin Tallec
Pierre Harvey Richemond
...
M. G. Azar
Bilal Piot
Koray Kavukcuoglu
Rémi Munos
Michal Valko
SSL
107
6,655
0
13 Jun 2020
Towards Understanding Cooperative Multi-Agent Q-Learning with Value
  Factorization
Towards Understanding Cooperative Multi-Agent Q-Learning with Value Factorization
Jianhao Wang
Zhizhou Ren
Beining Han
Jianing Ye
Chongjie Zhang
OffRL
21
32
0
31 May 2020
Better Exploration with Optimistic Actor-Critic
Better Exploration with Optimistic Actor-Critic
K. Ciosek
Q. Vuong
R. Loftin
Katja Hofmann
11
148
0
28 Oct 2019
Diagnosing Bottlenecks in Deep Q-learning Algorithms
Diagnosing Bottlenecks in Deep Q-learning Algorithms
Justin Fu
Aviral Kumar
Matthew Soh
Sergey Levine
OffRL
16
141
0
26 Feb 2019
A Survey and Critique of Multiagent Deep Reinforcement Learning
A Survey and Critique of Multiagent Deep Reinforcement Learning
Pablo Hernandez-Leal
Bilal Kartal
Matthew E. Taylor
OffRL
32
550
0
12 Oct 2018
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