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Dopamine: A Research Framework for Deep Reinforcement Learning

Dopamine: A Research Framework for Deep Reinforcement Learning

14 December 2018
Pablo Samuel Castro
Subhodeep Moitra
Carles Gelada
Saurabh Kumar
Marc G. Bellemare
    OffRL
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Papers citing "Dopamine: A Research Framework for Deep Reinforcement Learning"

49 / 49 papers shown
Title
Dynamic Learning Rate for Deep Reinforcement Learning: A Bandit Approach
Dynamic Learning Rate for Deep Reinforcement Learning: A Bandit Approach
Henrique Donâncio
Antoine Barrier
Leah F. South
Florence Forbes
23
0
0
16 Oct 2024
Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL
Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL
Ghada Sokar
J. Obando-Ceron
Aaron C. Courville
Hugo Larochelle
Pablo Samuel Castro
MoE
127
2
0
02 Oct 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
14
0
05 Jul 2024
The Curse of Diversity in Ensemble-Based Exploration
The Curse of Diversity in Ensemble-Based Exploration
Zhixuan Lin
P. DÓro
Evgenii Nikishin
Aaron C. Courville
42
1
0
07 May 2024
XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library
XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library
Wenzhang Liu
Wenzhe Cai
Kun Jiang
Guangran Cheng
Yuanda Wang
Changyin Sun
Jingyu Cao
Lele Xu
Chaoxu Mu
Changyin Sun
36
4
0
25 Dec 2023
An Invitation to Deep Reinforcement Learning
An Invitation to Deep Reinforcement Learning
Bernhard Jaeger
Andreas Geiger
OffRL
OOD
78
5
0
13 Dec 2023
EduGym: An Environment and Notebook Suite for Reinforcement Learning
  Education
EduGym: An Environment and Notebook Suite for Reinforcement Learning Education
Thomas M. Moerland
Matthias Muller-Brockhausen
Zhao Yang
Andrius Bernatavicius
Koen Ponse
Tom Kouwenhoven
Andreas Sauter
Michiel van der Meer
Bram M. Renting
Aske Plaat
OffRL
31
0
0
17 Nov 2023
A Kernel Perspective on Behavioural Metrics for Markov Decision
  Processes
A Kernel Perspective on Behavioural Metrics for Markov Decision Processes
Pablo Samuel Castro
Tyler Kastner
Prakash Panangaden
Mark Rowland
38
4
0
05 Oct 2023
Bigger, Better, Faster: Human-level Atari with human-level efficiency
Bigger, Better, Faster: Human-level Atari with human-level efficiency
Max Schwarzer
J. Obando-Ceron
Aaron C. Courville
Marc G. Bellemare
Rishabh Agarwal
Pablo Samuel Castro
OffRL
48
82
0
30 May 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
Karolos: An Open-Source Reinforcement Learning Framework for Robot-Task
  Environments
Karolos: An Open-Source Reinforcement Learning Framework for Robot-Task Environments
Christian Bitter
Timo Thun
Tobias Meisen
24
1
0
01 Dec 2022
Probing Transfer in Deep Reinforcement Learning without Task Engineering
Probing Transfer in Deep Reinforcement Learning without Task Engineering
Andrei A. Rusu
Sebastian Flennerhag
Dushyant Rao
Razvan Pascanu
R. Hadsell
34
6
0
22 Oct 2022
Hyperbolic Deep Reinforcement Learning
Hyperbolic Deep Reinforcement Learning
Edoardo Cetin
B. Chamberlain
Michael M. Bronstein
Jonathan J. Hunt
43
20
0
04 Oct 2022
Lamarckian Platform: Pushing the Boundaries of Evolutionary
  Reinforcement Learning towards Asynchronous Commercial Games
Lamarckian Platform: Pushing the Boundaries of Evolutionary Reinforcement Learning towards Asynchronous Commercial Games
Hui Bai
R. Shen
Yue Lin
Bo Xu
Ran Cheng
VLM
31
5
0
21 Sep 2022
Learning to Generalize with Object-centric Agents in the Open World
  Survival Game Crafter
Learning to Generalize with Object-centric Agents in the Open World Survival Game Crafter
Aleksandar Stanić
Yujin Tang
David R Ha
Jürgen Schmidhuber
ELM
29
13
0
05 Aug 2022
Reincarnating Reinforcement Learning: Reusing Prior Computation to
  Accelerate Progress
Reincarnating Reinforcement Learning: Reusing Prior Computation to Accelerate Progress
Rishabh Agarwal
Max Schwarzer
Pablo Samuel Castro
Aaron C. Courville
Marc G. Bellemare
OffRL
OnRL
26
63
0
03 Jun 2022
Orchestrated Value Mapping for Reinforcement Learning
Orchestrated Value Mapping for Reinforcement Learning
Mehdi Fatemi
Arash Tavakoli
19
8
0
14 Mar 2022
Consistent Dropout for Policy Gradient Reinforcement Learning
Consistent Dropout for Policy Gradient Reinforcement Learning
Matthew J. Hausknecht
Nolan Wagener
OffRL
19
10
0
23 Feb 2022
d3rlpy: An Offline Deep Reinforcement Learning Library
d3rlpy: An Offline Deep Reinforcement Learning Library
Takuma Seno
M. Imai
OffRL
GP
60
100
0
06 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
On Bonus-Based Exploration Methods in the Arcade Learning Environment
On Bonus-Based Exploration Methods in the Arcade Learning Environment
Adrien Ali Taïga
W. Fedus
Marlos C. Machado
Aaron Courville
Marc G. Bellemare
16
58
0
22 Sep 2021
Benchmarking the Spectrum of Agent Capabilities
Benchmarking the Spectrum of Agent Capabilities
Danijar Hafner
ELM
27
127
0
14 Sep 2021
Deep Reinforcement Learning at the Edge of the Statistical Precipice
Deep Reinforcement Learning at the Edge of the Statistical Precipice
Rishabh Agarwal
Max Schwarzer
Pablo Samuel Castro
Aaron Courville
Marc G. Bellemare
OffRL
56
633
0
30 Aug 2021
Tianshou: a Highly Modularized Deep Reinforcement Learning Library
Tianshou: a Highly Modularized Deep Reinforcement Learning Library
Jiayi Weng
Huayu Chen
Dong Yan
Kaichao You
Alexis Duburcq
Minghao Zhang
Yi Su
Hang Su
Jun Zhu
NoLa
OffRL
16
194
0
29 Jul 2021
Simplifying Deep Reinforcement Learning via Self-Supervision
Simplifying Deep Reinforcement Learning via Self-Supervision
Daochen Zha
Kwei-Herng Lai
Kaixiong Zhou
Xia Hu
SSL
28
15
0
10 Jun 2021
MICo: Improved representations via sampling-based state similarity for
  Markov decision processes
MICo: Improved representations via sampling-based state similarity for Markov decision processes
Pablo Samuel Castro
Tyler Kastner
Prakash Panangaden
Mark Rowland
40
35
0
03 Jun 2021
Spectral Normalisation for Deep Reinforcement Learning: an Optimisation
  Perspective
Spectral Normalisation for Deep Reinforcement Learning: an Optimisation Perspective
Florin Gogianu
Tudor Berariu
Mihaela Rosca
Claudia Clopath
L. Buşoniu
Razvan Pascanu
18
52
0
11 May 2021
Avalanche: an End-to-End Library for Continual Learning
Avalanche: an End-to-End Library for Continual Learning
Vincenzo Lomonaco
Lorenzo Pellegrini
Andrea Cossu
Antonio Carta
G. Graffieti
...
Christopher Kanan
J. Weijer
Tinne Tuytelaars
D. Bacciu
Davide Maltoni
BDL
AI4TS
28
180
0
01 Apr 2021
RecSim NG: Toward Principled Uncertainty Modeling for Recommender
  Ecosystems
RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems
Martin Mladenov
Chih-Wei Hsu
Vihan Jain
Eugene Ie
Christopher Colby
Nicolas Mayoraz
H. Pham
Dustin Tran
Ivan Vendrov
Craig Boutilier
BDL
15
31
0
14 Mar 2021
Faults in Deep Reinforcement Learning Programs: A Taxonomy and A
  Detection Approach
Faults in Deep Reinforcement Learning Programs: A Taxonomy and A Detection Approach
Amin Nikanjam
Mohammad Mehdi Morovati
Foutse Khomh
Houssem Ben Braiek
27
30
0
01 Jan 2021
TLeague: A Framework for Competitive Self-Play based Distributed
  Multi-Agent Reinforcement Learning
TLeague: A Framework for Competitive Self-Play based Distributed Multi-Agent Reinforcement Learning
Peng Sun
Jiechao Xiong
Lei Han
Xinghai Sun
Shuxing Li
Jiawei Xu
Meng Fang
Zhengyou Zhang
OffRL
LRM
25
19
0
25 Nov 2020
RLlib Flow: Distributed Reinforcement Learning is a Dataflow Problem
RLlib Flow: Distributed Reinforcement Learning is a Dataflow Problem
Eric Liang
Zhanghao Wu
Michael Luo
Sven Mika
Joseph E. Gonzalez
Ion Stoica
AI4CE
21
9
0
25 Nov 2020
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
9
105
0
20 Nov 2020
Mastering Atari with Discrete World Models
Mastering Atari with Discrete World Models
Danijar Hafner
Timothy Lillicrap
Mohammad Norouzi
Jimmy Ba
DRL
48
810
0
05 Oct 2020
Review: Deep Learning in Electron Microscopy
Review: Deep Learning in Electron Microscopy
Jeffrey M. Ede
34
79
0
17 Sep 2020
Acme: A Research Framework for Distributed Reinforcement Learning
Acme: A Research Framework for Distributed Reinforcement Learning
Matthew W. Hoffman
Bobak Shahriari
John Aslanides
Gabriel Barth-Maron
Nikola Momchev
...
Srivatsan Srinivasan
A. Cowie
Ziyun Wang
Bilal Piot
Nando de Freitas
54
225
0
01 Jun 2020
First return, then explore
First return, then explore
Adrien Ecoffet
Joost Huizinga
Joel Lehman
Kenneth O. Stanley
Jeff Clune
47
349
0
27 Apr 2020
Leverage the Average: an Analysis of KL Regularization in RL
Leverage the Average: an Analysis of KL Regularization in RL
Nino Vieillard
Tadashi Kozuno
B. Scherrer
Olivier Pietquin
Rémi Munos
M. Geist
17
42
0
31 Mar 2020
Fiber: A Platform for Efficient Development and Distributed Training for
  Reinforcement Learning and Population-Based Methods
Fiber: A Platform for Efficient Development and Distributed Training for Reinforcement Learning and Population-Based Methods
Jiale Zhi
Rui Wang
Jeff Clune
Kenneth O. Stanley
OffRL
22
12
0
25 Mar 2020
Enhanced Adversarial Strategically-Timed Attacks against Deep
  Reinforcement Learning
Enhanced Adversarial Strategically-Timed Attacks against Deep Reinforcement Learning
Chao-Han Huck Yang
Jun Qi
Pin-Yu Chen
Ouyang Yi
I-Te Danny Hung
Chin-Hui Lee
Xiaoli Ma
AAML
13
29
0
20 Feb 2020
SLM Lab: A Comprehensive Benchmark and Modular Software Framework for
  Reproducible Deep Reinforcement Learning
SLM Lab: A Comprehensive Benchmark and Modular Software Framework for Reproducible Deep Reinforcement Learning
Keng Wah Loon
L. Graesser
Milan Cvitkovic
OffRL
16
13
0
28 Dec 2019
Soft Actor-Critic for Discrete Action Settings
Soft Actor-Critic for Discrete Action Settings
Petros Christodoulou
OffRL
104
292
0
16 Oct 2019
Benchmarking Batch Deep Reinforcement Learning Algorithms
Benchmarking Batch Deep Reinforcement Learning Algorithms
Shih-Han Chou
Wen-Yen Chang
W. Hsu
Jianlong Fu
OffRL
13
181
0
03 Oct 2019
RecSim: A Configurable Simulation Platform for Recommender Systems
RecSim: A Configurable Simulation Platform for Recommender Systems
Eugene Ie
Chih-Wei Hsu
Martin Mladenov
Vihan Jain
Sanmit Narvekar
Jing Wang
Rui Wu
Craig Boutilier
16
177
0
11 Sep 2019
rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch
rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch
Adam Stooke
Pieter Abbeel
OffRL
16
96
0
03 Sep 2019
Is Deep Reinforcement Learning Really Superhuman on Atari? Leveling the
  playing field
Is Deep Reinforcement Learning Really Superhuman on Atari? Leveling the playing field
Marin Toromanoff
É. Wirbel
Fabien Moutarde
OffRL
22
24
0
13 Aug 2019
Behaviour Suite for Reinforcement Learning
Behaviour Suite for Reinforcement Learning
Ian Osband
Yotam Doron
Matteo Hessel
John Aslanides
Eren Sezener
...
Satinder Singh
Benjamin Van Roy
R. Sutton
David Silver
H. V. Hasselt
OffRL
24
178
0
09 Aug 2019
Hyperbolic Discounting and Learning over Multiple Horizons
Hyperbolic Discounting and Learning over Multiple Horizons
W. Fedus
Carles Gelada
Yoshua Bengio
Marc G. Bellemare
Hugo Larochelle
18
105
0
19 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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