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1510.09142
Cited By
Learning Continuous Control Policies by Stochastic Value Gradients
30 October 2015
N. Heess
Greg Wayne
David Silver
Timothy Lillicrap
Yuval Tassa
Tom Erez
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Papers citing
"Learning Continuous Control Policies by Stochastic Value Gradients"
50 / 337 papers shown
Better Exploration with Optimistic Actor-Critic
Neural Information Processing Systems (NeurIPS), 2019
K. Ciosek
Q. Vuong
R. Loftin
Katja Hofmann
204
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28 Oct 2019
Asynchronous Methods for Model-Based Reinforcement Learning
Conference on Robot Learning (CoRL), 2019
Yunzhi Zhang
I. Clavera
Bo-Yu Tsai
Pieter Abbeel
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133
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0
28 Oct 2019
OffWorld Gym: open-access physical robotics environment for real-world reinforcement learning benchmark and research
Ashish Kumar
Toby Buckley
John B. Lanier
Qiaozhi Wang
A. Kavelaars
Ilya Kuzovkin
OffRL
247
15
0
18 Oct 2019
Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models
Conference on Robot Learning (CoRL), 2019
Arunkumar Byravan
Jost Tobias Springenberg
A. Abdolmaleki
Agrim Gupta
Michael Neunert
Thomas Lampe
Noah Y. Siegel
N. Heess
Martin Riedmiller
OffRL
181
44
0
09 Oct 2019
If MaxEnt RL is the Answer, What is the Question?
Benjamin Eysenbach
Sergey Levine
157
65
0
04 Oct 2019
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control
International Conference on Learning Representations (ICLR), 2019
H. F. Song
A. Abdolmaleki
Jost Tobias Springenberg
Aidan Clark
Hubert Soyer
...
Dhruva Tirumala
N. Heess
Dan Belov
Martin Riedmiller
M. Botvinick
252
134
0
26 Sep 2019
Constrained Attractor Selection Using Deep Reinforcement Learning
Journal of Vibration and Control (JVC), 2019
Xue-She Wang
J. Turner
B. Mann
90
36
0
23 Sep 2019
Gradient-Aware Model-based Policy Search
AAAI Conference on Artificial Intelligence (AAAI), 2019
P. DÓro
Alberto Maria Metelli
Andrea Tirinzoni
Matteo Papini
Marcello Restelli
217
38
0
09 Sep 2019
Deterministic Value-Policy Gradients
AAAI Conference on Artificial Intelligence (AAAI), 2019
Qingpeng Cai
L. Pan
Pingzhong Tang
172
1
0
09 Sep 2019
DeepHealth: Review and challenges of artificial intelligence in health informatics
Gloria Hyunjung Kwak
Pan Hui
SyDa
211
26
0
01 Sep 2019
Deep Reinforcement Learning for Clinical Decision Support: A Brief Survey
Siqi Liu
K. Ngiam
Mengling Feng
LM&MA
OffRL
137
21
0
22 Jul 2019
Benchmarking Model-Based Reinforcement Learning
Tingwu Wang
Xuchan Bao
I. Clavera
Jerrick Hoang
Yeming Wen
Eric D. Langlois
Matthew Shunshi Zhang
Guodong Zhang
Pieter Abbeel
Jimmy Ba
OffRL
271
385
0
03 Jul 2019
Compositional Transfer in Hierarchical Reinforcement Learning
Markus Wulfmeier
A. Abdolmaleki
Agrim Gupta
Jost Tobias Springenberg
Michael Neunert
Tim Hertweck
Thomas Lampe
Noah Y. Siegel
N. Heess
Martin Riedmiller
231
28
0
26 Jun 2019
Monte Carlo Gradient Estimation in Machine Learning
Journal of machine learning research (JMLR), 2019
S. Mohamed
Mihaela Rosca
Michael Figurnov
A. Mnih
345
472
0
25 Jun 2019
Exploring Model-based Planning with Policy Networks
International Conference on Learning Representations (ICLR), 2019
Tingwu Wang
Jimmy Ba
304
160
0
20 Jun 2019
When to Trust Your Model: Model-Based Policy Optimization
Neural Information Processing Systems (NeurIPS), 2019
Michael Janner
Justin Fu
Marvin Zhang
Sergey Levine
OffRL
395
1,097
0
19 Jun 2019
Robust Reinforcement Learning for Continuous Control with Model Misspecification
International Conference on Learning Representations (ICLR), 2019
D. Mankowitz
Nir Levine
Rae Jeong
Yuanyuan Shi
Jackie Kay
A. Abdolmaleki
Jost Tobias Springenberg
Timothy A. Mann
Todd Hester
Martin Riedmiller
OOD
238
129
0
18 Jun 2019
Direct Policy Gradients: Direct Optimization of Policies in Discrete Action Spaces
Neural Information Processing Systems (NeurIPS), 2019
Guy Lorberbom
Chris J. Maddison
N. Heess
Tamir Hazan
Daniel Tarlow
212
8
0
14 Jun 2019
Improving Exploration in Soft-Actor-Critic with Normalizing Flows Policies
Patrick Nadeem Ward
Ariella Smofsky
A. Bose
150
61
0
06 Jun 2019
An Introduction to Variational Autoencoders
Diederik P. Kingma
Max Welling
BDL
SSL
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738
2,783
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06 Jun 2019
Harnessing Reinforcement Learning for Neural Motion Planning
Tom Jurgenson
Aviv Tamar
OOD
262
67
0
01 Jun 2019
On the Generalization Gap in Reparameterizable Reinforcement Learning
International Conference on Machine Learning (ICML), 2019
Huan Wang
Stephan Zheng
Caiming Xiong
R. Socher
213
42
0
29 May 2019
MQLV: Optimal Policy of Money Management in Retail Banking with Q-Learning
Jérémy Charlier
Gaston Ormazabal
R. State
Jean Hilger
OffRL
123
3
0
24 May 2019
Random Expert Distillation: Imitation Learning via Expert Policy Support Estimation
International Conference on Machine Learning (ICML), 2019
Ruohan Wang
C. Ciliberto
P. Amadori
Y. Demiris
184
67
0
16 May 2019
Meta reinforcement learning as task inference
Jan Humplik
Alexandre Galashov
Leonard Hasenclever
Pedro A. Ortega
Yee Whye Teh
N. Heess
OffRL
383
136
0
15 May 2019
Fast Skill Learning for Variable Compliance Robotic Assembly
Tianyu Ren
Yunfei Dong
Dan Wu
Ken Chen
74
2
0
11 May 2019
Do Autonomous Agents Benefit from Hearing?
Abraham Woubie
Anssi Kanervisto
Janne Karttunen
Ville Hautamaki
98
8
0
10 May 2019
Information asymmetry in KL-regularized RL
International Conference on Learning Representations (ICLR), 2019
Alexandre Galashov
Siddhant M. Jayakumar
Leonard Hasenclever
Dhruva Tirumala
Jonathan Richard Schwarz
Guillaume Desjardins
Wojciech M. Czarnecki
Yee Whye Teh
Razvan Pascanu
N. Heess
OffRL
174
104
0
03 May 2019
Stochastic Lipschitz Q-Learning
Xu Zhu
200
4
0
24 Apr 2019
Only Relevant Information Matters: Filtering Out Noisy Samples to Boost RL
Yannis Flet-Berliac
Philippe Preux
307
2
0
08 Apr 2019
Structured agents for physical construction
V. Bapst
Alvaro Sanchez-Gonzalez
Carl Doersch
Kimberly L. Stachenfeld
Pushmeet Kohli
Peter W. Battaglia
Jessica B. Hamrick
AI4CE
281
103
0
05 Apr 2019
Multitask Soft Option Learning
Maximilian Igl
Andrew Gambardella
Jinke He
Nantas Nardelli
N. Siddharth
Wendelin Bohmer
Shimon Whiteson
346
26
0
01 Apr 2019
Meta-Learning surrogate models for sequential decision making
Alexandre Galashov
Jonathan Richard Schwarz
Hyunjik Kim
M. Garnelo
D. Saxton
Pushmeet Kohli
S. M. Ali Eslami
Yee Whye Teh
BDL
OffRL
220
25
0
28 Mar 2019
Constructing Parsimonious Analytic Models for Dynamic Systems via Symbolic Regression
Erik Derner
Jiří Kubalík
N. Ancona
Robert Babuška
109
10
0
27 Mar 2019
Exploiting Hierarchy for Learning and Transfer in KL-regularized RL
Dhruva Tirumala
Hyeonwoo Noh
Alexandre Galashov
Leonard Hasenclever
Arun Ahuja
Greg Wayne
Razvan Pascanu
Yee Whye Teh
N. Heess
OffRL
167
45
0
18 Mar 2019
Dyna-AIL : Adversarial Imitation Learning by Planning
Vaibhav Saxena
Srinivasan Sivanandan
Pulkit Mathur
100
1
0
08 Mar 2019
Hybrid Actor-Critic Reinforcement Learning in Parameterized Action Space
International Joint Conference on Artificial Intelligence (IJCAI), 2019
Zhou Fan
Ruilong Su
Weinan Zhang
Yong Yu
338
191
0
04 Mar 2019
Model-Based Reinforcement Learning for Atari
International Conference on Learning Representations (ICLR), 2019
Lukasz Kaiser
Mohammad Babaeizadeh
Piotr Milos
B. Osinski
R. Campbell
...
Sergey Levine
Afroz Mohiuddin
Ryan Sepassi
George Tucker
Henryk Michalewski
OffRL
858
946
0
01 Mar 2019
Emergent Coordination Through Competition
Siqi Liu
Guy Lever
J. Merel
S. Tunyasuvunakool
N. Heess
T. Graepel
291
157
0
19 Feb 2019
Simultaneously Learning Vision and Feature-based Control Policies for Real-world Ball-in-a-Cup
Devin Schwab
Tobias Springenberg
M. Martins
Thomas Lampe
Michael Neunert
A. Abdolmaleki
Tim Hertweck
Agrim Gupta
F. Nori
Martin Riedmiller
168
22
0
13 Feb 2019
Total stochastic gradient algorithms and applications in reinforcement learning
Paavo Parmas
139
18
0
05 Feb 2019
Probability Functional Descent: A Unifying Perspective on GANs, Variational Inference, and Reinforcement Learning
International Conference on Machine Learning (ICML), 2019
Casey Chu
Jose H. Blanchet
Peter Glynn
GAN
201
28
0
30 Jan 2019
Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic
Mikael Henaff
A. Canziani
Yann LeCun
OOD
362
127
0
08 Jan 2019
Credit Assignment Techniques in Stochastic Computation Graphs
T. Weber
N. Heess
Lars Buesing
David Silver
169
47
0
07 Jan 2019
VMAV-C: A Deep Attention-based Reinforcement Learning Algorithm for Model-based Control
Xingxing Liang
Qi Wang
Yanghe Feng
Zhong Liu
Jincai Huang
121
5
0
24 Dec 2018
Residual Policy Learning
Tom Silver
Kelsey R. Allen
J. Tenenbaum
L. Kaelbling
OffRL
459
199
0
15 Dec 2018
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
1.1K
2,892
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13 Dec 2018
Relative Entropy Regularized Policy Iteration
A. Abdolmaleki
Jost Tobias Springenberg
Jonas Degrave
Steven Bohez
Yuval Tassa
Dan Belov
N. Heess
Martin Riedmiller
136
75
0
05 Dec 2018
An Introduction to Deep Reinforcement Learning
Vincent François-Lavet
Peter Henderson
Riashat Islam
Marc G. Bellemare
Joelle Pineau
OffRL
AI4CE
413
1,406
0
30 Nov 2018
Neural probabilistic motor primitives for humanoid control
J. Merel
Leonard Hasenclever
Alexandre Galashov
Arun Ahuja
Vu Pham
Greg Wayne
Yee Whye Teh
N. Heess
285
176
0
28 Nov 2018
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