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Probing Transfer in Deep Reinforcement Learning without Task Engineering

Probing Transfer in Deep Reinforcement Learning without Task Engineering

22 October 2022
Andrei A. Rusu
Sebastian Flennerhag
Dushyant Rao
Razvan Pascanu
R. Hadsell
ArXivPDFHTML

Papers citing "Probing Transfer in Deep Reinforcement Learning without Task Engineering"

37 / 37 papers shown
Title
The Option Keyboard: Combining Skills in Reinforcement Learning
The Option Keyboard: Combining Skills in Reinforcement Learning
André Barreto
Diana Borsa
Shaobo Hou
Gheorghe Comanici
Eser Aygun
...
Daniel Toyama
Jonathan J. Hunt
Shibl Mourad
David Silver
Doina Precup
61
99
0
24 Jun 2021
Mastering Atari with Discrete World Models
Mastering Atari with Discrete World Models
Danijar Hafner
Timothy Lillicrap
Mohammad Norouzi
Jimmy Ba
DRL
95
852
0
05 Oct 2020
Transfer Learning in Deep Reinforcement Learning: A Survey
Transfer Learning in Deep Reinforcement Learning: A Survey
Zhuangdi Zhu
Kaixiang Lin
Anil K. Jain
Jiayu Zhou
OffRL
LRM
107
589
0
16 Sep 2020
Meta-Learning in Neural Networks: A Survey
Meta-Learning in Neural Networks: A Survey
Timothy M. Hospedales
Antreas Antoniou
P. Micaelli
Amos Storkey
OOD
375
1,974
0
11 Apr 2020
Dota 2 with Large Scale Deep Reinforcement Learning
Dota 2 with Large Scale Deep Reinforcement Learning
OpenAI OpenAI
:
Christopher Berner
Greg Brockman
Brooke Chan
...
Szymon Sidor
Ilya Sutskever
Jie Tang
Filip Wolski
Susan Zhang
GNN
VLM
CLL
AI4CE
LRM
140
1,822
0
13 Dec 2019
Leveraging Procedural Generation to Benchmark Reinforcement Learning
Leveraging Procedural Generation to Benchmark Reinforcement Learning
K. Cobbe
Christopher Hesse
Jacob Hilton
John Schulman
72
555
0
03 Dec 2019
Meta-World: A Benchmark and Evaluation for Multi-Task and Meta
  Reinforcement Learning
Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning
Tianhe Yu
Deirdre Quillen
Zhanpeng He
Ryan Julian
Avnish Narayan
Hayden Shively
Adithya Bellathur
Karol Hausman
Chelsea Finn
Sergey Levine
OffRL
224
1,165
0
24 Oct 2019
Dopamine: A Research Framework for Deep Reinforcement Learning
Dopamine: A Research Framework for Deep Reinforcement Learning
Pablo Samuel Castro
Subhodeep Moitra
Carles Gelada
Saurabh Kumar
Marc G. Bellemare
OffRL
65
278
0
14 Dec 2018
Quantifying Generalization in Reinforcement Learning
Quantifying Generalization in Reinforcement Learning
K. Cobbe
Oleg Klimov
Christopher Hesse
Taehoon Kim
John Schulman
OffRL
91
670
0
06 Dec 2018
The Barbados 2018 List of Open Issues in Continual Learning
The Barbados 2018 List of Open Issues in Continual Learning
Tom Schaul
H. V. Hasselt
Joseph Modayil
Martha White
Adam White
Pierre-Luc Bacon
J. Harb
Shibl Mourad
Marc G. Bellemare
Doina Precup
LM&Ro
3DV
36
10
0
16 Nov 2018
Generalization and Regularization in DQN
Generalization and Regularization in DQN
Jesse Farebrother
Marlos C. Machado
Michael Bowling
84
205
0
29 Sep 2018
Implicit Quantile Networks for Distributional Reinforcement Learning
Implicit Quantile Networks for Distributional Reinforcement Learning
Will Dabney
Georg Ostrovski
David Silver
Rémi Munos
OffRL
129
531
0
14 Jun 2018
Kickstarting Deep Reinforcement Learning
Kickstarting Deep Reinforcement Learning
Simon Schmitt
Jonathan J. Hudson
Augustin Žídek
Simon Osindero
Carl Doersch
...
Joel Z Leibo
Heinrich Küttler
Andrew Zisserman
Karen Simonyan
S. M. Ali Eslami
OnRL
52
132
0
10 Mar 2018
Distributed Prioritized Experience Replay
Distributed Prioritized Experience Replay
Dan Horgan
John Quan
David Budden
Gabriel Barth-Maron
Matteo Hessel
H. V. Hasselt
David Silver
143
740
0
02 Mar 2018
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement
  Learning with a Stochastic Actor
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
Tuomas Haarnoja
Aurick Zhou
Pieter Abbeel
Sergey Levine
290
8,329
0
04 Jan 2018
Rainbow: Combining Improvements in Deep Reinforcement Learning
Rainbow: Combining Improvements in Deep Reinforcement Learning
Matteo Hessel
Joseph Modayil
H. V. Hasselt
Tom Schaul
Georg Ostrovski
Will Dabney
Dan Horgan
Bilal Piot
M. G. Azar
David Silver
OffRL
107
2,263
0
06 Oct 2017
Revisiting the Arcade Learning Environment: Evaluation Protocols and
  Open Problems for General Agents
Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents
Marlos C. Machado
Marc G. Bellemare
Erik Talvitie
J. Veness
Matthew J. Hausknecht
Michael Bowling
71
552
0
18 Sep 2017
A Distributional Perspective on Reinforcement Learning
A Distributional Perspective on Reinforcement Learning
Marc G. Bellemare
Will Dabney
Rémi Munos
OffRL
93
1,503
0
21 Jul 2017
Proximal Policy Optimization Algorithms
Proximal Policy Optimization Algorithms
John Schulman
Filip Wolski
Prafulla Dhariwal
Alec Radford
Oleg Klimov
OffRL
453
19,006
0
20 Jul 2017
Noisy Networks for Exploration
Noisy Networks for Exploration
Meire Fortunato
M. G. Azar
Bilal Piot
Jacob Menick
Ian Osband
...
Rémi Munos
Demis Hassabis
Olivier Pietquin
Charles Blundell
Shane Legg
79
893
0
30 Jun 2017
Domain Randomization for Transferring Deep Neural Networks from
  Simulation to the Real World
Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World
Joshua Tobin
Rachel Fong
Alex Ray
Jonas Schneider
Wojciech Zaremba
Pieter Abbeel
238
2,964
0
20 Mar 2017
Reinforcement Learning with Unsupervised Auxiliary Tasks
Reinforcement Learning with Unsupervised Auxiliary Tasks
Max Jaderberg
Volodymyr Mnih
Wojciech M. Czarnecki
Tom Schaul
Joel Z Leibo
David Silver
Koray Kavukcuoglu
SSL
101
1,228
0
16 Nov 2016
Sample Efficient Actor-Critic with Experience Replay
Sample Efficient Actor-Critic with Experience Replay
Ziyun Wang
V. Bapst
N. Heess
Volodymyr Mnih
Rémi Munos
Koray Kavukcuoglu
Nando de Freitas
97
761
0
03 Nov 2016
Sim-to-Real Robot Learning from Pixels with Progressive Nets
Sim-to-Real Robot Learning from Pixels with Progressive Nets
Andrei A. Rusu
Matej Vecerík
Thomas Rothörl
N. Heess
Razvan Pascanu
R. Hadsell
72
533
0
13 Oct 2016
Successor Features for Transfer in Reinforcement Learning
Successor Features for Transfer in Reinforcement Learning
André Barreto
Will Dabney
Rémi Munos
Jonathan J. Hunt
Tom Schaul
H. V. Hasselt
David Silver
45
575
0
16 Jun 2016
Progressive Neural Networks
Progressive Neural Networks
Andrei A. Rusu
Neil C. Rabinowitz
Guillaume Desjardins
Hubert Soyer
J. Kirkpatrick
Koray Kavukcuoglu
Razvan Pascanu
R. Hadsell
CLL
AI4CE
77
2,446
0
15 Jun 2016
Asynchronous Methods for Deep Reinforcement Learning
Asynchronous Methods for Deep Reinforcement Learning
Volodymyr Mnih
Adria Puigdomenech Badia
M. Berk Mirza
Alex Graves
Timothy Lillicrap
Tim Harley
David Silver
Koray Kavukcuoglu
191
8,850
0
04 Feb 2016
Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning
Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning
Emilio Parisotto
Jimmy Lei Ba
Ruslan Salakhutdinov
OffRL
83
599
0
19 Nov 2015
Policy Distillation
Policy Distillation
Andrei A. Rusu
Sergio Gomez Colmenarejo
Çağlar Gülçehre
Guillaume Desjardins
J. Kirkpatrick
Razvan Pascanu
Volodymyr Mnih
Koray Kavukcuoglu
R. Hadsell
81
692
0
19 Nov 2015
Prioritized Experience Replay
Prioritized Experience Replay
Tom Schaul
John Quan
Ioannis Antonoglou
David Silver
OffRL
212
3,787
0
18 Nov 2015
Deep Reinforcement Learning with Double Q-learning
Deep Reinforcement Learning with Double Q-learning
H. V. Hasselt
A. Guez
David Silver
OffRL
156
7,635
0
22 Sep 2015
Continuous control with deep reinforcement learning
Continuous control with deep reinforcement learning
Timothy Lillicrap
Jonathan J. Hunt
Alexander Pritzel
N. Heess
Tom Erez
Yuval Tassa
David Silver
Daan Wierstra
318
13,234
0
09 Sep 2015
End-to-End Training of Deep Visuomotor Policies
End-to-End Training of Deep Visuomotor Policies
Sergey Levine
Chelsea Finn
Trevor Darrell
Pieter Abbeel
BDL
302
3,434
0
02 Apr 2015
Trust Region Policy Optimization
Trust Region Policy Optimization
John Schulman
Sergey Levine
Philipp Moritz
Michael I. Jordan
Pieter Abbeel
277
6,764
0
19 Feb 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.7K
150,006
0
22 Dec 2014
Playing Atari with Deep Reinforcement Learning
Playing Atari with Deep Reinforcement Learning
Volodymyr Mnih
Koray Kavukcuoglu
David Silver
Alex Graves
Ioannis Antonoglou
Daan Wierstra
Martin Riedmiller
117
12,223
0
19 Dec 2013
The Arcade Learning Environment: An Evaluation Platform for General
  Agents
The Arcade Learning Environment: An Evaluation Platform for General Agents
Marc G. Bellemare
Yavar Naddaf
J. Veness
Michael Bowling
109
3,004
0
19 Jul 2012
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