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Continuous control with deep reinforcement learning
v1v2v3v4v5v6 (latest)

Continuous control with deep reinforcement learning

9 September 2015
Timothy Lillicrap
Jonathan J. Hunt
Alexander Pritzel
N. Heess
Tom Erez
Yuval Tassa
David Silver
Daan Wierstra
ArXiv (abs)PDFHTML

Papers citing "Continuous control with deep reinforcement learning"

46 / 4,796 papers shown
Sim-to-Real Robot Learning from Pixels with Progressive Nets
Sim-to-Real Robot Learning from Pixels with Progressive NetsConference on Robot Learning (CoRL), 2016
Andrei A. Rusu
Matej Vecerík
Thomas Rothörl
N. Heess
Razvan Pascanu
R. Hadsell
328
552
0
13 Oct 2016
Learning Feedback Terms for Reactive Planning and Control
Learning Feedback Terms for Reactive Planning and ControlIEEE International Conference on Robotics and Automation (ICRA), 2016
Akshara Rai
Giovanni Sutanto
S. Schaal
Franziska Meier
139
42
0
11 Oct 2016
Connecting Generative Adversarial Networks and Actor-Critic Methods
Connecting Generative Adversarial Networks and Actor-Critic Methods
David Pfau
Oriol Vinyals
OffRLAI4CE
303
189
0
06 Oct 2016
Towards Cognitive Exploration through Deep Reinforcement Learning for
  Mobile Robots
Towards Cognitive Exploration through Deep Reinforcement Learning for Mobile Robots
L. Tai
Ming-Yuan Liu
100
113
0
06 Oct 2016
EPOpt: Learning Robust Neural Network Policies Using Model Ensembles
EPOpt: Learning Robust Neural Network Policies Using Model EnsemblesInternational Conference on Learning Representations (ICLR), 2016
Aravind Rajeswaran
Sarvjeet Ghotra
Balaraman Ravindran
Sergey Levine
604
374
0
05 Oct 2016
Reset-Free Guided Policy Search: Efficient Deep Reinforcement Learning
  with Stochastic Initial States
Reset-Free Guided Policy Search: Efficient Deep Reinforcement Learning with Stochastic Initial StatesIEEE International Conference on Robotics and Automation (ICRA), 2016
William H. Montgomery
Anurag Ajay
Chelsea Finn
Pieter Abbeel
Sergey Levine
OnRL
238
39
0
04 Oct 2016
Deep Visual Foresight for Planning Robot Motion
Deep Visual Foresight for Planning Robot Motion
Chelsea Finn
Sergey Levine
377
834
0
03 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
219
159
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
316
1,545
0
03 Oct 2016
Path Integral Guided Policy Search
Path Integral Guided Policy Search
Yevgen Chebotar
Mrinal Kalakrishnan
Ali Yahya
A. Li
S. Schaal
Sergey Levine
268
152
0
03 Oct 2016
Deep Reinforcement Learning for Tensegrity Robot Locomotion
Deep Reinforcement Learning for Tensegrity Robot Locomotion
Marvin Zhang
Xinyang Geng
J. Bruce
Ken Caluwaerts
Massimo Vespignani
Vytas SunSpiral
Pieter Abbeel
Sergey Levine
203
102
0
28 Sep 2016
Input Convex Neural Networks
Input Convex Neural Networks
Brandon Amos
Lei Xu
J. Zico Kolter
931
744
0
22 Sep 2016
Learning Modular Neural Network Policies for Multi-Task and Multi-Robot
  Transfer
Learning Modular Neural Network Policies for Multi-Task and Multi-Robot Transfer
Coline Devin
Abhishek Gupta
Trevor Darrell
Pieter Abbeel
Sergey Levine
OffRL
194
427
0
22 Sep 2016
3D Simulation for Robot Arm Control with Deep Q-Learning
3D Simulation for Robot Arm Control with Deep Q-Learning
Stephen James
Edward Johns
236
110
0
13 Sep 2016
Partially Observable Markov Decision Process for Recommender Systems
Partially Observable Markov Decision Process for Recommender Systems
Zhongqi Lu
Qiang Yang
198
29
0
28 Aug 2016
An Actor-Critic Algorithm for Sequence Prediction
An Actor-Critic Algorithm for Sequence Prediction
Dzmitry Bahdanau
Philemon Brakel
Kelvin Xu
Anirudh Goyal
Ryan J. Lowe
Joelle Pineau
Aaron Courville
Yoshua Bengio
317
660
0
24 Jul 2016
Guided Policy Search as Approximate Mirror Descent
Guided Policy Search as Approximate Mirror DescentNeural Information Processing Systems (NeurIPS), 2016
William H. Montgomery
Sergey Levine
163
127
0
15 Jul 2016
Actor-critic versus direct policy search: a comparison based on sample
  complexity
Actor-critic versus direct policy search: a comparison based on sample complexity
Arnaud de Froissard de Broissia
Olivier Sigaud
120
13
0
29 Jun 2016
Learning to Poke by Poking: Experiential Learning of Intuitive Physics
Learning to Poke by Poking: Experiential Learning of Intuitive PhysicsNeural Information Processing Systems (NeurIPS), 2016
Pulkit Agrawal
Ashvin Nair
Pieter Abbeel
Jitendra Malik
Sergey Levine
SSL
366
594
0
23 Jun 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
204
631
0
16 Jun 2016
Deep Reinforcement Learning with a Combinatorial Action Space for
  Predicting Popular Reddit Threads
Deep Reinforcement Learning with a Combinatorial Action Space for Predicting Popular Reddit Threads
Ji He
Mari Ostendorf
Xiaodong He
Jianshu Chen
Jianfeng Gao
Lihong Li
Li Deng
248
4
0
12 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
189
316
0
29 May 2016
Review of state-of-the-arts in artificial intelligence with application
  to AI safety problem
Review of state-of-the-arts in artificial intelligence with application to AI safety problem
V. Shakirov
149
10
0
11 May 2016
Convolutional Neural Networks For Automatic State-Time Feature
  Extraction in Reinforcement Learning Applied to Residential Load Control
Convolutional Neural Networks For Automatic State-Time Feature Extraction in Reinforcement Learning Applied to Residential Load Control
Bert Claessens
Peter Vrancx
F. Ruelens
140
129
0
28 Apr 2016
Benchmarking Deep Reinforcement Learning for Continuous Control
Benchmarking Deep Reinforcement Learning for Continuous Control
Yan Duan
Xi Chen
Rein Houthooft
John Schulman
Pieter Abbeel
OffRL
476
1,768
0
22 Apr 2016
Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning
  and Large-Scale Data Collection
Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning and Large-Scale Data Collection
Sergey Levine
P. Pastor
A. Krizhevsky
Deirdre Quillen
1.1K
2,152
0
07 Mar 2016
Learning Physical Intuition of Block Towers by Example
Learning Physical Intuition of Block Towers by Example
Adam Lerer
Sam Gross
Rob Fergus
PINN
261
308
0
03 Mar 2016
Deep Reinforcement Learning from Self-Play in Imperfect-Information
  Games
Deep Reinforcement Learning from Self-Play in Imperfect-Information Games
Johannes Heinrich
David Silver
SSL
240
432
0
03 Mar 2016
PLATO: Policy Learning using Adaptive Trajectory Optimization
PLATO: Policy Learning using Adaptive Trajectory Optimization
G. Kahn
Tianhao Zhang
Sergey Levine
Pieter Abbeel
290
139
0
02 Mar 2016
Towards Neural Knowledge DNA
Towards Neural Knowledge DNA
Haoxi Zhang
C. Sanín
E. Szczerbicki
60
16
0
27 Feb 2016
Bayesian Optimization with Safety Constraints: Safe and Automatic
  Parameter Tuning in Robotics
Bayesian Optimization with Safety Constraints: Safe and Automatic Parameter Tuning in Robotics
Felix Berkenkamp
Andreas Krause
Angela P. Schoellig
471
321
0
14 Feb 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
770
9,645
0
04 Feb 2016
Deep Reinforcement Learning in Large Discrete Action Spaces
Deep Reinforcement Learning in Large Discrete Action Spaces
Gabriel Dulac-Arnold
Richard Evans
H. V. Hasselt
P. Sunehag
Timothy Lillicrap
Jonathan J. Hunt
Timothy A. Mann
T. Weber
T. Degris
Ben Coppin
OffRL
339
606
0
24 Dec 2015
Memory-based control with recurrent neural networks
Memory-based control with recurrent neural networks
N. Heess
Jonathan J. Hunt
Timothy Lillicrap
David Silver
252
320
0
14 Dec 2015
Gated networks: an inventory
Gated networks: an inventory
Olivier Sigaud
Clément Masson
David Filliat
F. Stulp
157
19
0
10 Dec 2015
Q-Networks for Binary Vector Actions
Q-Networks for Binary Vector Actions
N. Yoshida
OffRLMQ
73
3
0
04 Dec 2015
Deep Reinforcement Learning with Attention for Slate Markov Decision
  Processes with High-Dimensional States and Actions
Deep Reinforcement Learning with Attention for Slate Markov Decision Processes with High-Dimensional States and Actions
P. Sunehag
Richard Evans
Gabriel Dulac-Arnold
Yori Zwols
D. Visentin
Ben Coppin
305
46
0
03 Dec 2015
Learning Visual Predictive Models of Physics for Playing Billiards
Learning Visual Predictive Models of Physics for Playing Billiards
Katerina Fragkiadaki
Pulkit Agrawal
Sergey Levine
Jitendra Malik
298
274
0
23 Nov 2015
Adapting Deep Visuomotor Representations with Weak Pairwise Constraints
Adapting Deep Visuomotor Representations with Weak Pairwise Constraints
Eric Tzeng
Coline Devin
Judy Hoffman
Chelsea Finn
Pieter Abbeel
Sergey Levine
Kate Saenko
Trevor Darrell
OOD
373
144
0
23 Nov 2015
Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning
Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning
Emilio Parisotto
Jimmy Lei Ba
Ruslan Salakhutdinov
OffRL
290
627
0
19 Nov 2015
Deep Reinforcement Learning with a Natural Language Action Space
Deep Reinforcement Learning with a Natural Language Action Space
Ji He
Jianshu Chen
Xiaodong He
Jianfeng Gao
Lihong Li
Li Deng
Mari Ostendorf
392
257
0
14 Nov 2015
Deep Reinforcement Learning in Parameterized Action Space
Deep Reinforcement Learning in Parameterized Action Space
Matthew J. Hausknecht
Peter Stone
352
326
0
13 Nov 2015
Learning Continuous Control Policies by Stochastic Value Gradients
Learning Continuous Control Policies by Stochastic Value Gradients
N. Heess
Greg Wayne
David Silver
Timothy Lillicrap
Yuval Tassa
Tom Erez
250
583
0
30 Oct 2015
Semantics, Representations and Grammars for Deep Learning
Semantics, Representations and Grammars for Deep Learning
David Balduzzi
GNN
130
2
0
29 Sep 2015
High-Dimensional Continuous Control Using Generalized Advantage
  Estimation
High-Dimensional Continuous Control Using Generalized Advantage EstimationInternational Conference on Learning Representations (ICLR), 2015
John Schulman
Philipp Moritz
Sergey Levine
Sai Li
Pieter Abbeel
OffRL
768
4,030
0
08 Jun 2015
End-to-End Training of Deep Visuomotor Policies
End-to-End Training of Deep Visuomotor PoliciesJournal of machine learning research (JMLR), 2015
Sergey Levine
Chelsea Finn
Trevor Darrell
Pieter Abbeel
BDL
806
3,635
0
02 Apr 2015
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