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Asynchronous Methods for Deep Reinforcement Learning
v1v2 (latest)

Asynchronous Methods for Deep Reinforcement Learning

4 February 2016
Volodymyr Mnih
Adria Puigdomenech Badia
M. Berk Mirza
Alex Graves
Timothy Lillicrap
Tim Harley
David Silver
Koray Kavukcuoglu
ArXiv (abs)PDFHTML

Papers citing "Asynchronous Methods for Deep Reinforcement Learning"

41 / 3,591 papers shown
Title
Learning to Perform Physics Experiments via Deep Reinforcement Learning
Learning to Perform Physics Experiments via Deep Reinforcement Learning
Misha Denil
Pulkit Agrawal
Tejas D. Kulkarni
Tom Erez
Peter W. Battaglia
Nando de Freitas
AI4CE
113
333
0
06 Nov 2016
Learning to Act by Predicting the Future
Learning to Act by Predicting the Future
Alexey Dosovitskiy
V. Koltun
189
281
0
06 Nov 2016
Combining policy gradient and Q-learning
Combining policy gradient and Q-learning
Brendan O'Donoghue
Rémi Munos
Koray Kavukcuoglu
Volodymyr Mnih
OffRLOnRL
109
140
0
05 Nov 2016
Learning to Play in a Day: Faster Deep Reinforcement Learning by
  Optimality Tightening
Learning to Play in a Day: Faster Deep Reinforcement Learning by Optimality Tightening
Frank S. He
Yang Liu
Alex Schwing
Jian-wei Peng
91
84
0
05 Nov 2016
Multi-task learning with deep model based reinforcement learning
Multi-task learning with deep model based reinforcement learning
Asier Mujika
58
9
0
04 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
131
763
0
03 Nov 2016
Learning Runtime Parameters in Computer Systems with Delayed Experience
  Injection
Learning Runtime Parameters in Computer Systems with Delayed Experience Injection
Michael Schaarschmidt
Felix Gessert
Valentin Dalibard
Eiko Yoneki
30
9
0
31 Oct 2016
Using Fast Weights to Attend to the Recent Past
Using Fast Weights to Attend to the Recent Past
Jimmy Ba
Geoffrey E. Hinton
Volodymyr Mnih
Joel Z Leibo
Catalin Ionescu
101
273
0
20 Oct 2016
Learning and Transfer of Modulated Locomotor Controllers
Learning and Transfer of Modulated Locomotor Controllers
N. Heess
Greg Wayne
Yuval Tassa
Timothy Lillicrap
Martin Riedmiller
David Silver
99
208
0
17 Oct 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
128
535
0
13 Oct 2016
Deep Reinforcement Learning From Raw Pixels in Doom
Deep Reinforcement Learning From Raw Pixels in Doom
Danijar Hafner
25
5
0
07 Oct 2016
Connecting Generative Adversarial Networks and Actor-Critic Methods
Connecting Generative Adversarial Networks and Actor-Critic Methods
David Pfau
Oriol Vinyals
OffRLAI4CE
124
186
0
06 Oct 2016
Collective Robot Reinforcement Learning with Distributed Asynchronous
  Guided Policy Search
Collective Robot Reinforcement Learning with Distributed Asynchronous Guided Policy Search
Ali Yahya
A. Li
Mrinal Kalakrishnan
Yevgen Chebotar
Sergey Levine
OffRL
99
155
0
03 Oct 2016
Deep Reinforcement Learning for Robotic Manipulation with Asynchronous
  Off-Policy Updates
Deep Reinforcement Learning for Robotic Manipulation with Asynchronous Off-Policy Updates
S. Gu
E. Holly
Timothy Lillicrap
Sergey Levine
OffRLSSL
167
1,485
0
03 Oct 2016
Target-driven Visual Navigation in Indoor Scenes using Deep
  Reinforcement Learning
Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement Learning
Yuke Zhu
Roozbeh Mottaghi
Eric Kolve
Joseph J. Lim
Abhinav Gupta
Li Fei-Fei
Ali Farhadi
VGen
133
1,529
0
16 Sep 2016
The Option-Critic Architecture
The Option-Critic Architecture
Pierre-Luc Bacon
J. Harb
Doina Precup
OffRL
116
1,090
0
16 Sep 2016
Exploration Potential
Exploration Potential
Jan Leike
53
10
0
16 Sep 2016
A Threshold-based Scheme for Reinforcement Learning in Neural Networks
A Threshold-based Scheme for Reinforcement Learning in Neural Networks
Thomas H. Ward
41
0
0
12 Sep 2016
Reward Augmented Maximum Likelihood for Neural Structured Prediction
Reward Augmented Maximum Likelihood for Neural Structured Prediction
Mohammad Norouzi
Samy Bengio
Zhiwen Chen
Navdeep Jaitly
M. Schuster
Yonghui Wu
Dale Schuurmans
118
253
0
01 Sep 2016
Strategic Attentive Writer for Learning Macro-Actions
Strategic Attentive Writer for Learning Macro-Actions
Alexander
A. Vezhnevets
Volodymyr Mnih
J. Agapiou
Simon Osindero
Alex Graves
Oriol Vinyals
Koray Kavukcuoglu
67
171
0
15 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
CLLAI4CE
101
2,468
0
15 Jun 2016
Deep Reinforcement Learning With Macro-Actions
Deep Reinforcement Learning With Macro-Actions
Ishan Durugkar
Clemens Rosenbaum
S. Dernbach
Sridhar Mahadevan
58
25
0
15 Jun 2016
Model-Free Episodic Control
Model-Free Episodic Control
Charles Blundell
Benigno Uria
Alexander Pritzel
Yazhe Li
Avraham Ruderman
Joel Z Leibo
Jack W. Rae
Daan Wierstra
Demis Hassabis
OffRLBDL
59
250
0
14 Jun 2016
Memory-Efficient Backpropagation Through Time
Memory-Efficient Backpropagation Through Time
A. Gruslys
Rémi Munos
Ivo Danihelka
Marc Lanctot
Alex Graves
99
229
0
10 Jun 2016
Policy Networks with Two-Stage Training for Dialogue Systems
Policy Networks with Two-Stage Training for Dialogue Systems
Mehdi Fatemi
Layla El Asri
Hannes Schulz
Jing He
Kaheer Suleman
OffRL
88
108
0
10 Jun 2016
Safe and Efficient Off-Policy Reinforcement Learning
Safe and Efficient Off-Policy Reinforcement Learning
Rémi Munos
T. Stepleton
Anna Harutyunyan
Marc G. Bellemare
OffRL
177
619
0
08 Jun 2016
Deep Successor Reinforcement Learning
Deep Successor Reinforcement Learning
Tejas D. Kulkarni
A. Saeedi
Simanta Gautam
S. Gershman
80
209
0
08 Jun 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
195
1,487
0
06 Jun 2016
OpenAI Gym
OpenAI Gym
Greg Brockman
Vicki Cheung
Ludwig Pettersson
Jonas Schneider
John Schulman
Jie Tang
Wojciech Zaremba
OffRLODL
342
5,095
0
05 Jun 2016
Predicting Personal Traits from Facial Images using Convolutional Neural
  Networks Augmented with Facial Landmark Information
Predicting Personal Traits from Facial Images using Convolutional Neural Networks Augmented with Facial Landmark Information
Yoad Lewenberg
Valliappa Chockalingam
Satinder Singh
Honglak Lee
CVBM
78
305
0
29 May 2016
Dynamic Frame skip Deep Q Network
Dynamic Frame skip Deep Q Network
A. Srinivas
Sahil Sharma
Balaraman Ravindran
78
23
0
17 May 2016
Option Discovery in Hierarchical Reinforcement Learning using
  Spatio-Temporal Clustering
Option Discovery in Hierarchical Reinforcement Learning using Spatio-Temporal Clustering
A. Srinivas
Ramnandan Krishnamurthy
Peeyush Kumar
Balaraman Ravindran
89
41
0
17 May 2016
A Deep Hierarchical Approach to Lifelong Learning in Minecraft
A Deep Hierarchical Approach to Lifelong Learning in Minecraft
Chen Tessler
Shahar Givony
Tom Zahavy
D. Mankowitz
Shie Mannor
CLL
181
381
0
25 Apr 2016
Hierarchical Deep Reinforcement Learning: Integrating Temporal
  Abstraction and Intrinsic Motivation
Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation
Tejas D. Kulkarni
Karthik Narasimhan
A. Saeedi
J. Tenenbaum
131
1,144
0
20 Apr 2016
Easy Monotonic Policy Iteration
Easy Monotonic Policy Iteration
Joshua Achiam
OffRL
49
0
0
29 Feb 2016
Learning values across many orders of magnitude
Learning values across many orders of magnitude
H. V. Hasselt
A. Guez
Matteo Hessel
Volodymyr Mnih
David Silver
88
170
0
24 Feb 2016
Value Iteration Networks
Value Iteration Networks
Aviv Tamar
Yi Wu
G. Thomas
Sergey Levine
Pieter Abbeel
150
657
0
09 Feb 2016
State of the Art Control of Atari Games Using Shallow Reinforcement
  Learning
State of the Art Control of Atari Games Using Shallow Reinforcement Learning
Yitao Liang
Marlos C. Machado
Erik Talvitie
Michael Bowling
105
113
0
04 Dec 2015
NetVLAD: CNN architecture for weakly supervised place recognition
NetVLAD: CNN architecture for weakly supervised place recognition
Relja Arandjelović
Petr Gronát
Akihiko Torii
Tomas Pajdla
Josef Sivic
3DVSSL
151
2,659
0
23 Nov 2015
Exclusive Sparsity Norm Minimization with Random Groups via Cone
  Projection
Exclusive Sparsity Norm Minimization with Random Groups via Cone Projection
Yijun Huang
Ji Liu
71
8
0
27 Oct 2015
Attend, Adapt and Transfer: Attentive Deep Architecture for Adaptive
  Transfer from multiple sources in the same domain
Attend, Adapt and Transfer: Attentive Deep Architecture for Adaptive Transfer from multiple sources in the same domain
Janarthanan Rajendran
A. Srinivas
Mitesh M. Khapra
Prasanna Parthasarathi
Balaraman Ravindran
59
52
0
10 Oct 2015
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