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Decoupled Exploration and Exploitation Policies for Sample-Efficient
  Reinforcement Learning

Decoupled Exploration and Exploitation Policies for Sample-Efficient Reinforcement Learning

23 January 2021
William F. Whitney
Michael Bloesch
Jost Tobias Springenberg
A. Abdolmaleki
Kyunghyun Cho
Martin Riedmiller
    OffRL
ArXivPDFHTML

Papers citing "Decoupled Exploration and Exploitation Policies for Sample-Efficient Reinforcement Learning"

33 / 33 papers shown
Title
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
47
59
0
22 Sep 2021
Temporally-Extended ε-Greedy Exploration
Temporally-Extended ε-Greedy Exploration
Will Dabney
Georg Ostrovski
André Barreto
46
34
0
02 Jun 2020
Kernel Operations on the GPU, with Autodiff, without Memory Overflows
Kernel Operations on the GPU, with Autodiff, without Memory Overflows
Benjamin Charlier
Jean Feydy
J. Glaunès
François-David Collin
G. Durif
38
177
0
27 Mar 2020
Optimistic Exploration even with a Pessimistic Initialisation
Optimistic Exploration even with a Pessimistic Initialisation
Tabish Rashid
Bei Peng
Wendelin Bohmer
Shimon Whiteson
OffRL
OnRL
37
44
0
26 Feb 2020
Never Give Up: Learning Directed Exploration Strategies
Never Give Up: Learning Directed Exploration Strategies
Adria Puigdomenech Badia
Pablo Sprechmann
Alex Vitvitskyi
Daniel Guo
Bilal Piot
...
O. Tieleman
Martín Arjovsky
Alexander Pritzel
Andew Bolt
Charles Blundell
70
298
0
14 Feb 2020
Continuous-Discrete Reinforcement Learning for Hybrid Control in
  Robotics
Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics
Michael Neunert
A. Abdolmaleki
Markus Wulfmeier
Thomas Lampe
Jost Tobias Springenberg
Roland Hafner
Francesco Romano
J. Buchli
N. Heess
Martin Riedmiller
59
91
0
02 Jan 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
434
42,393
0
03 Dec 2019
Dynamics-aware Embeddings
Dynamics-aware Embeddings
William F. Whitney
Rajat Agarwal
Kyunghyun Cho
Abhinav Gupta
SSL
54
53
0
25 Aug 2019
Soft Actor-Critic Algorithms and Applications
Soft Actor-Critic Algorithms and Applications
Tuomas Haarnoja
Aurick Zhou
Kristian Hartikainen
George Tucker
Sehoon Ha
...
Vikash Kumar
Henry Zhu
Abhishek Gupta
Pieter Abbeel
Sergey Levine
133
2,422
0
13 Dec 2018
Exploration by Random Network Distillation
Exploration by Random Network Distillation
Yuri Burda
Harrison Edwards
Amos Storkey
Oleg Klimov
153
1,329
0
30 Oct 2018
Count-Based Exploration with the Successor Representation
Count-Based Exploration with the Successor Representation
Marlos C. Machado
Marc G. Bellemare
Michael Bowling
46
186
0
31 Jul 2018
Is Q-learning Provably Efficient?
Is Q-learning Provably Efficient?
Chi Jin
Zeyuan Allen-Zhu
Sébastien Bubeck
Michael I. Jordan
OffRL
63
806
0
10 Jul 2018
QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic
  Manipulation
QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation
Dmitry Kalashnikov
A. Irpan
P. Pastor
Julian Ibarz
Alexander Herzog
...
Deirdre Quillen
E. Holly
Mrinal Kalakrishnan
Vincent Vanhoucke
Sergey Levine
113
1,460
0
27 Jun 2018
Maximum a Posteriori Policy Optimisation
Maximum a Posteriori Policy Optimisation
A. Abdolmaleki
Jost Tobias Springenberg
Yuval Tassa
Rémi Munos
N. Heess
Martin Riedmiller
71
477
0
14 Jun 2018
Learning by Playing - Solving Sparse Reward Tasks from Scratch
Learning by Playing - Solving Sparse Reward Tasks from Scratch
Martin Riedmiller
Roland Hafner
Thomas Lampe
Michael Neunert
Jonas Degrave
T. Wiele
Volodymyr Mnih
N. Heess
Jost Tobias Springenberg
83
448
0
28 Feb 2018
Addressing Function Approximation Error in Actor-Critic Methods
Addressing Function Approximation Error in Actor-Critic Methods
Scott Fujimoto
H. V. Hoof
David Meger
OffRL
169
5,178
0
26 Feb 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
292
8,329
0
04 Jan 2018
DeepMind Control Suite
DeepMind Control Suite
Yuval Tassa
Yotam Doron
Alistair Muldal
Tom Erez
Yazhe Li
...
A. Abdolmaleki
J. Merel
Andrew Lefrancq
Timothy Lillicrap
Martin Riedmiller
ELM
LM&Ro
BDL
127
1,133
0
02 Jan 2018
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
Parameter Space Noise for Exploration
Parameter Space Noise for Exploration
Matthias Plappert
Rein Houthooft
Prafulla Dhariwal
Szymon Sidor
Richard Y. Chen
Xi Chen
Tamim Asfour
Pieter Abbeel
Marcin Andrychowicz
52
595
0
06 Jun 2017
Curiosity-driven Exploration by Self-supervised Prediction
Curiosity-driven Exploration by Self-supervised Prediction
Deepak Pathak
Pulkit Agrawal
Alexei A. Efros
Trevor Darrell
LRM
SSL
106
2,436
0
15 May 2017
Data-efficient Deep Reinforcement Learning for Dexterous Manipulation
Data-efficient Deep Reinforcement Learning for Dexterous Manipulation
I. Popov
N. Heess
Timothy Lillicrap
Roland Hafner
Gabriel Barth-Maron
Matej Vecerík
Thomas Lampe
Yuval Tassa
Tom Erez
Martin Riedmiller
OffRL
69
264
0
10 Apr 2017
Deep Exploration via Randomized Value Functions
Deep Exploration via Randomized Value Functions
Ian Osband
Benjamin Van Roy
Daniel Russo
Zheng Wen
89
306
0
22 Mar 2017
Count-Based Exploration with Neural Density Models
Count-Based Exploration with Neural Density Models
Georg Ostrovski
Marc G. Bellemare
Aaron van den Oord
Rémi Munos
84
620
0
03 Mar 2017
#Exploration: A Study of Count-Based Exploration for Deep Reinforcement
  Learning
#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning
Haoran Tang
Rein Houthooft
Davis Foote
Adam Stooke
Xi Chen
Yan Duan
John Schulman
F. Turck
Pieter Abbeel
OffRL
89
771
0
15 Nov 2016
Unifying Count-Based Exploration and Intrinsic Motivation
Unifying Count-Based Exploration and Intrinsic Motivation
Marc G. Bellemare
S. Srinivasan
Georg Ostrovski
Tom Schaul
D. Saxton
Rémi Munos
167
1,477
0
06 Jun 2016
Deep Exploration via Bootstrapped DQN
Deep Exploration via Bootstrapped DQN
Ian Osband
Charles Blundell
Alexander Pritzel
Benjamin Van Roy
121
1,307
0
15 Feb 2016
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
158
7,635
0
22 Sep 2015
Pareto Smoothed Importance Sampling
Pareto Smoothed Importance Sampling
Aki Vehtari
Daniel Simpson
Andrew Gelman
Yuling Yao
Jonah Gabry
66
242
0
09 Jul 2015
Incentivizing Exploration In Reinforcement Learning With Deep Predictive
  Models
Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models
Bradly C. Stadie
Sergey Levine
Pieter Abbeel
89
505
0
03 Jul 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
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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