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Asynchronous Methods for Deep Reinforcement Learning

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
ArXivPDFHTML

Papers citing "Asynchronous Methods for Deep Reinforcement Learning"

50 / 1,710 papers shown
Title
An End-to-End Approach to Natural Language Object Retrieval via
  Context-Aware Deep Reinforcement Learning
An End-to-End Approach to Natural Language Object Retrieval via Context-Aware Deep Reinforcement Learning
Fan Wu
Zhongwen Xu
Yi Yang
ObjD
34
11
0
22 Mar 2017
Learning to Navigate Cloth using Haptics
Learning to Navigate Cloth using Haptics
Alexander Clegg
Wenhao Yu
Zackory M. Erickson
Jie Tan
Chenxi Liu
Greg Turk
29
23
0
20 Mar 2017
Evolution Strategies as a Scalable Alternative to Reinforcement Learning
Evolution Strategies as a Scalable Alternative to Reinforcement Learning
Tim Salimans
Jonathan Ho
Xi Chen
Szymon Sidor
Ilya Sutskever
45
1,517
0
10 Mar 2017
Tactics of Adversarial Attack on Deep Reinforcement Learning Agents
Tactics of Adversarial Attack on Deep Reinforcement Learning Agents
Yen-Chen Lin
Zhang-Wei Hong
Yuan-Hong Liao
Meng-Li Shih
Ming-Yuan Liu
Min Sun
AAML
28
411
0
08 Mar 2017
Neural Episodic Control
Neural Episodic Control
Alexander Pritzel
Benigno Uria
Sriram Srinivasan
A. Badia
Oriol Vinyals
Demis Hassabis
Daan Wierstra
Charles Blundell
OffRL
BDL
35
345
0
06 Mar 2017
Surprise-Based Intrinsic Motivation for Deep Reinforcement Learning
Surprise-Based Intrinsic Motivation for Deep Reinforcement Learning
Joshua Achiam
S. Shankar Sastry
40
235
0
06 Mar 2017
Virtual-to-real Deep Reinforcement Learning: Continuous Control of
  Mobile Robots for Mapless Navigation
Virtual-to-real Deep Reinforcement Learning: Continuous Control of Mobile Robots for Mapless Navigation
L. Tai
Giuseppe Paolo
Ming-Yuan Liu
28
704
0
01 Mar 2017
Bridging the Gap Between Value and Policy Based Reinforcement Learning
Bridging the Gap Between Value and Policy Based Reinforcement Learning
Ofir Nachum
Mohammad Norouzi
Kelvin Xu
Dale Schuurmans
38
468
0
28 Feb 2017
Learning What Data to Learn
Learning What Data to Learn
Yang Fan
Fei Tian
Tao Qin
Jiang Bian
Tie-Yan Liu
18
79
0
28 Feb 2017
Learning Control for Air Hockey Striking using Deep Reinforcement
  Learning
Learning Control for Air Hockey Striking using Deep Reinforcement Learning
Ayal Taitler
N. Shimkin
23
10
0
26 Feb 2017
Online Meta-learning by Parallel Algorithm Competition
Online Meta-learning by Parallel Algorithm Competition
Stefan Elfwing
E. Uchibe
Kenji Doya
31
22
0
24 Feb 2017
Deep Models Under the GAN: Information Leakage from Collaborative Deep
  Learning
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning
Briland Hitaj
G. Ateniese
Fernando Perez-Cruz
FedML
77
1,382
0
24 Feb 2017
Active One-shot Learning
Active One-shot Learning
Mark P. Woodward
Chelsea Finn
VLM
OffRL
13
130
0
21 Feb 2017
Real-time visual tracking by deep reinforced decision making
Real-time visual tracking by deep reinforced decision making
Janghoon Choi
Junseok Kwon
Kyoung Mu Lee
16
41
0
21 Feb 2017
Learning to Multi-Task by Active Sampling
Learning to Multi-Task by Active Sampling
Sahil Sharma
Ashutosh Jha
Parikshit Hegde
Balaraman Ravindran
21
21
0
20 Feb 2017
Sigmoid-Weighted Linear Units for Neural Network Function Approximation
  in Reinforcement Learning
Sigmoid-Weighted Linear Units for Neural Network Function Approximation in Reinforcement Learning
Stefan Elfwing
E. Uchibe
Kenji Doya
24
1,674
0
10 Feb 2017
Preparing for the Unknown: Learning a Universal Policy with Online
  System Identification
Preparing for the Unknown: Learning a Universal Policy with Online System Identification
Wenhao Yu
Jie Tan
Chenxi Liu
Greg Turk
OffRL
42
306
0
08 Feb 2017
DeepNav: Learning to Navigate Large Cities
DeepNav: Learning to Navigate Large Cities
Samarth Brahmbhatt
James Hays
SSL
HAI
19
53
0
31 Jan 2017
Wasserstein GAN
Wasserstein GAN
Martín Arjovsky
Soumith Chintala
Léon Bottou
GAN
78
4,809
0
26 Jan 2017
Learning Light Transport the Reinforced Way
Learning Light Transport the Reinforced Way
Ken Dahm
A. Keller
29
63
0
25 Jan 2017
Deep Reinforcement Learning: An Overview
Deep Reinforcement Learning: An Overview
Yuxi Li
OffRL
VLM
121
1,508
0
25 Jan 2017
Regularizing Neural Networks by Penalizing Confident Output
  Distributions
Regularizing Neural Networks by Penalizing Confident Output Distributions
Gabriel Pereyra
George Tucker
J. Chorowski
Lukasz Kaiser
Geoffrey E. Hinton
NoLa
78
1,127
0
23 Jan 2017
The Predictron: End-To-End Learning and Planning
The Predictron: End-To-End Learning and Planning
David Silver
H. V. Hasselt
Matteo Hessel
Tom Schaul
A. Guez
...
Gabriel Dulac-Arnold
David P. Reichert
Neil C. Rabinowitz
André Barreto
T. Degris
23
289
0
28 Dec 2016
Loss is its own Reward: Self-Supervision for Reinforcement Learning
Loss is its own Reward: Self-Supervision for Reinforcement Learning
Evan Shelhamer
Parsa Mahmoudieh
Max Argus
Trevor Darrell
SSL
24
186
0
21 Dec 2016
DeepMind Lab
DeepMind Lab
Charlie Beattie
Joel Z Leibo
Denis Teplyashin
Tom Ward
Marcus Wainwright
...
Stephen Gaffney
Helen King
Demis Hassabis
Shane Legg
Stig Petersen
22
240
0
12 Dec 2016
Towards better decoding and language model integration in sequence to
  sequence models
Towards better decoding and language model integration in sequence to sequence models
J. Chorowski
Navdeep Jaitly
17
368
0
08 Dec 2016
Combining Deep Reinforcement Learning and Safety Based Control for
  Autonomous Driving
Combining Deep Reinforcement Learning and Safety Based Control for Autonomous Driving
Xincheng Xiong
Jianqiang Wang
Fang Zhang
Keqiang Li
34
66
0
01 Dec 2016
Neural Combinatorial Optimization with Reinforcement Learning
Neural Combinatorial Optimization with Reinforcement Learning
Irwan Bello
Hieu H. Pham
Quoc V. Le
Mohammad Norouzi
Samy Bengio
71
1,462
0
29 Nov 2016
Nonparametric General Reinforcement Learning
Nonparametric General Reinforcement Learning
Jan Leike
OffRL
46
26
0
28 Nov 2016
Dense Captioning with Joint Inference and Visual Context
Dense Captioning with Joint Inference and Visual Context
L. Yang
K. Tang
Jianchao Yang
Li Li
VLM
35
169
0
21 Nov 2016
Local minima in training of neural networks
Local minima in training of neural networks
G. Swirszcz
Wojciech M. Czarnecki
Razvan Pascanu
ODL
37
73
0
19 Nov 2016
Learning to reinforcement learn
Learning to reinforcement learn
Jane X. Wang
Z. Kurth-Nelson
Dhruva Tirumala
Hubert Soyer
Joel Z Leibo
Rémi Munos
Charles Blundell
D. Kumaran
M. Botvinick
OffRL
19
975
0
17 Nov 2016
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
13
1,224
0
16 Nov 2016
#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
60
760
0
15 Nov 2016
How to scale distributed deep learning?
How to scale distributed deep learning?
Peter H. Jin
Qiaochu Yuan
F. Iandola
Kurt Keutzer
3DH
27
136
0
14 Nov 2016
RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning
RL2^22: Fast Reinforcement Learning via Slow Reinforcement Learning
Yan Duan
John Schulman
Xi Chen
Peter L. Bartlett
Ilya Sutskever
Pieter Abbeel
OffRL
35
1,010
0
09 Nov 2016
Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic
Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic
S. Gu
Timothy Lillicrap
Zoubin Ghahramani
Richard Turner
Sergey Levine
OffRL
BDL
47
343
0
07 Nov 2016
Playing SNES in the Retro Learning Environment
Playing SNES in the Retro Learning Environment
Nadav Bhonker
Shai Rozenberg
Itay Hubara
26
19
0
07 Nov 2016
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
46
338
0
06 Nov 2016
Learning to Act by Predicting the Future
Learning to Act by Predicting the Future
Alexey Dosovitskiy
V. Koltun
34
280
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
OffRL
OnRL
30
139
0
05 Nov 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
16
263
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
37
207
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
44
532
0
13 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
26
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
OffRL
SSL
56
1,473
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
30
1,513
0
16 Sep 2016
The Option-Critic Architecture
The Option-Critic Architecture
Pierre-Luc Bacon
J. Harb
Doina Precup
OffRL
21
1,071
0
16 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
35
252
0
01 Sep 2016
Memory-Efficient Backpropagation Through Time
Memory-Efficient Backpropagation Through Time
A. Gruslys
Rémi Munos
Ivo Danihelka
Marc Lanctot
Alex Graves
37
228
0
10 Jun 2016
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