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Solving Rubik's Cube with a Robot Hand

Solving Rubik's Cube with a Robot Hand

16 October 2019
OpenAI
Ilge Akkaya
Marcin Andrychowicz
Maciek Chociej
Ma-teusz Litwin
Bob McGrew
Arthur Petron
Alex Paino
Matthias Plappert
Glenn Powell
Raphael Ribas
Jonas Schneider
Nikolas Tezak
Jerry Tworek
Peter Welinder
Lilian Weng
Qiming Yuan
Wojciech Zaremba
Lei Zhang
    ODL
ArXiv (abs)PDFHTML

Papers citing "Solving Rubik's Cube with a Robot Hand"

50 / 775 papers shown
Title
An Imitation from Observation Approach to Transfer Learning with
  Dynamics Mismatch
An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch
Siddarth Desai
Ishan Durugkar
Haresh Karnan
Garrett A. Warnell
Josiah P. Hanna
Peter Stone
48
5
0
04 Aug 2020
Reinforced Grounded Action Transformation for Sim-to-Real Transfer
Reinforced Grounded Action Transformation for Sim-to-Real Transfer
Haresh Karnan
Siddharth Desai
Josiah P. Hanna
Garrett A. Warnell
Peter Stone
59
24
0
04 Aug 2020
Learning to Drive (L2D) as a Low-Cost Benchmark for Real-World
  Reinforcement Learning
Learning to Drive (L2D) as a Low-Cost Benchmark for Real-World Reinforcement Learning
A. Viitala
Rinu Boney
Yi Zhao
Alexander Ilin
Arno Solin
OffRL
57
7
0
03 Aug 2020
Single-Timescale Actor-Critic Provably Finds Globally Optimal Policy
Single-Timescale Actor-Critic Provably Finds Globally Optimal Policy
Zuyue Fu
Zhuoran Yang
Zhaoran Wang
87
43
0
02 Aug 2020
Queueing Network Controls via Deep Reinforcement Learning
Queueing Network Controls via Deep Reinforcement Learning
J. Dai
Mark O. Gluzman
OffRL
125
51
0
31 Jul 2020
Self-Adapting Recurrent Models for Object Pushing from Learning in
  Simulation
Self-Adapting Recurrent Models for Object Pushing from Learning in Simulation
Lin Cong
Michael Görner
Philipp Ruppel
Hongzhuo Liang
Norman Hendrich
Jianwei Zhang
99
13
0
27 Jul 2020
Learning Compositional Neural Programs for Continuous Control
Learning Compositional Neural Programs for Continuous Control
Thomas Pierrot
Nicolas Perrin
Feryal M. P. Behbahani
Alexandre Laterre
Olivier Sigaud
Karim Beguir
Nando de Freitas
CLL
95
4
0
27 Jul 2020
Probabilistic Active Meta-Learning
Probabilistic Active Meta-Learning
Jean Kaddour
Steindór Sæmundsson
M. Deisenroth
98
35
0
17 Jul 2020
Distributed Reinforcement Learning of Targeted Grasping with Active
  Vision for Mobile Manipulators
Distributed Reinforcement Learning of Targeted Grasping with Active Vision for Mobile Manipulators
Yasuhiro Fujita
Kota Uenishi
Avinash Ummadisingu
P. Nagarajan
Shimpei Masuda
M. Castro
84
18
0
16 Jul 2020
One Policy to Control Them All: Shared Modular Policies for
  Agent-Agnostic Control
One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control
Wenlong Huang
Igor Mordatch
Deepak Pathak
148
179
0
09 Jul 2020
Deep Reinforcement Learning and its Neuroscientific Implications
Deep Reinforcement Learning and its Neuroscientific Implications
M. Botvinick
Jane X. Wang
Will Dabney
Kevin J. Miller
Z. Kurth-Nelson
OffRLAI4CE
97
176
0
07 Jul 2020
robo-gym -- An Open Source Toolkit for Distributed Deep Reinforcement
  Learning on Real and Simulated Robots
robo-gym -- An Open Source Toolkit for Distributed Deep Reinforcement Learning on Real and Simulated Robots
M. Lucchi
Friedemann Zindler
Stephan Mühlbacher-Karrer
Horst Pichler
OffRL
86
30
0
06 Jul 2020
Adaptive Procedural Task Generation for Hard-Exploration Problems
Adaptive Procedural Task Generation for Hard-Exploration Problems
Kuan Fang
Yuke Zhu
Silvio Savarese
Li Fei-Fei
78
26
0
01 Jul 2020
Lipschitzness Is All You Need To Tame Off-policy Generative Adversarial
  Imitation Learning
Lipschitzness Is All You Need To Tame Off-policy Generative Adversarial Imitation Learning
Lionel Blondé
Pablo Strasser
Alexandros Kalousis
90
22
0
28 Jun 2020
Can Autonomous Vehicles Identify, Recover From, and Adapt to
  Distribution Shifts?
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?
Angelos Filos
P. Tigas
R. McAllister
Nicholas Rhinehart
Sergey Levine
Y. Gal
83
188
0
26 Jun 2020
Quantifying Differences in Reward Functions
Quantifying Differences in Reward Functions
Adam Gleave
Michael Dennis
Shane Legg
Stuart J. Russell
Jan Leike
OffRL
173
68
0
24 Jun 2020
RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning
RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning
Çağlar Gülçehre
Ziyun Wang
Alexander Novikov
T. Paine
Sergio Gomez Colmenarejo
...
Matthew W. Hoffman
Ofir Nachum
George Tucker
N. Heess
Nando de Freitas
OffRL
134
72
0
24 Jun 2020
Information Theoretic Regret Bounds for Online Nonlinear Control
Information Theoretic Regret Bounds for Online Nonlinear Control
Sham Kakade
A. Krishnamurthy
Kendall Lowrey
Motoya Ohnishi
Wen Sun
90
119
0
22 Jun 2020
Optimizing Interactive Systems via Data-Driven Objectives
Optimizing Interactive Systems via Data-Driven Objectives
Ziming Li
Julia Kiseleva
A. Grotov
Maarten de Rijke
Harrie Oosterhuis
OffRL
43
3
0
19 Jun 2020
Automatic Curriculum Learning through Value Disagreement
Automatic Curriculum Learning through Value Disagreement
Yunzhi Zhang
Pieter Abbeel
Lerrel Pinto
83
109
0
17 Jun 2020
Open Questions in Creating Safe Open-ended AI: Tensions Between Control
  and Creativity
Open Questions in Creating Safe Open-ended AI: Tensions Between Control and Creativity
Adrien Ecoffet
Jeff Clune
Joel Lehman
88
16
0
12 Jun 2020
TorsionNet: A Reinforcement Learning Approach to Sequential Conformer
  Search
TorsionNet: A Reinforcement Learning Approach to Sequential Conformer Search
T. Gogineni
Ziping Xu
E. Punzalan
Runxuan Jiang
Joshua A Kammeraad
Ambuj Tewari
Paul M. Zimmerman
AI4CE
62
32
0
12 Jun 2020
Mutual Information Based Knowledge Transfer Under State-Action Dimension
  Mismatch
Mutual Information Based Knowledge Transfer Under State-Action Dimension Mismatch
Michael Wan
Tanmay Gangwani
Jian-wei Peng
61
19
0
12 Jun 2020
Learning to Play by Imitating Humans
Learning to Play by Imitating Humans
R. Dinyari
P. Sermanet
Corey Lynch
SSLOffRL
46
5
0
11 Jun 2020
What Matters In On-Policy Reinforcement Learning? A Large-Scale
  Empirical Study
What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study
Marcin Andrychowicz
Anton Raichuk
Piotr Stańczyk
Manu Orsini
Sertan Girgin
...
Matthieu Geist
Olivier Pietquin
Marcin Michalski
Sylvain Gelly
Olivier Bachem
OffRL
92
226
0
10 Jun 2020
Learning compositional models of robot skills for task and motion
  planning
Learning compositional models of robot skills for task and motion planning
Zi Wang
Caelan Reed Garrett
L. Kaelbling
Tomás Lozano-Pérez
106
110
0
08 Jun 2020
Visual Transfer for Reinforcement Learning via Wasserstein Domain
  Confusion
Visual Transfer for Reinforcement Learning via Wasserstein Domain Confusion
Josh Roy
George Konidaris
73
16
0
04 Jun 2020
Learning Memory-Based Control for Human-Scale Bipedal Locomotion
Learning Memory-Based Control for Human-Scale Bipedal Locomotion
J. Siekmann
S. Valluri
Jeremy Dao
Lorenzo Bermillo
Helei Duan
Alan Fern
J. Hurst
AI4CE
67
71
0
03 Jun 2020
Interferobot: aligning an optical interferometer by a reinforcement
  learning agent
Interferobot: aligning an optical interferometer by a reinforcement learning agent
Dmitry Sorokin
Alexander Ulanov
E. A. Sazhina
A. Lvovsky
60
17
0
03 Jun 2020
Learning Active Task-Oriented Exploration Policies for Bridging the
  Sim-to-Real Gap
Learning Active Task-Oriented Exploration Policies for Bridging the Sim-to-Real Gap
Jacky Liang
Saumya Saxena
Oliver Kroemer
66
19
0
02 Jun 2020
Invariant Policy Optimization: Towards Stronger Generalization in
  Reinforcement Learning
Invariant Policy Optimization: Towards Stronger Generalization in Reinforcement Learning
Anoopkumar Sonar
Vincent Pacelli
Anirudha Majumdar
115
54
0
01 Jun 2020
LEAF: Latent Exploration Along the Frontier
LEAF: Latent Exploration Along the Frontier
Homanga Bharadhwaj
Animesh Garg
Florian Shkurti
70
1
0
21 May 2020
Reinforcement Learning with General Value Function Approximation:
  Provably Efficient Approach via Bounded Eluder Dimension
Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension
Ruosong Wang
Ruslan Salakhutdinov
Lin F. Yang
101
55
0
21 May 2020
Novel Policy Seeking with Constrained Optimization
Novel Policy Seeking with Constrained Optimization
Hao Sun
Zhenghao Peng
Bo Dai
Jian Guo
Dahua Lin
Bolei Zhou
138
13
0
21 May 2020
Deep Reinforcement Learning for High Level Character Control
Deep Reinforcement Learning for High Level Character Control
Caio Souza
Luiz Velho
AI4CE
102
0
0
20 May 2020
Automating Turbulence Modeling by Multi-Agent Reinforcement Learning
Automating Turbulence Modeling by Multi-Agent Reinforcement Learning
G. Novati
Hugues Lascombes de Laroussilhe
Petros Koumoutsakos
AI4CE
106
15
0
18 May 2020
DeepClaw: A Robotic Hardware Benchmarking Platform for Learning Object
  Manipulation
DeepClaw: A Robotic Hardware Benchmarking Platform for Learning Object Manipulation
Fang Wan
Haokun Wang
Xiaobo Liu
Linhan Yang
Chaoyang Song
34
4
0
06 May 2020
Open Loop In Natura Economic Planning
Open Loop In Natura Economic Planning
Spyridon Samothrakis
6
1
0
04 May 2020
Reinforcement Learning with Augmented Data
Reinforcement Learning with Augmented Data
Michael Laskin
Kimin Lee
Adam Stooke
Lerrel Pinto
Pieter Abbeel
A. Srinivas
OffRL
165
661
0
30 Apr 2020
Sim-to-Real Transfer with Incremental Environment Complexity for
  Reinforcement Learning of Depth-Based Robot Navigation
Sim-to-Real Transfer with Incremental Environment Complexity for Reinforcement Learning of Depth-Based Robot Navigation
Thomas Chaffre
Julien Moras
Adrien Chan-Hon-Tong
J. Marzat
40
36
0
30 Apr 2020
Meta-Reinforcement Learning for Robotic Industrial Insertion Tasks
Meta-Reinforcement Learning for Robotic Industrial Insertion Tasks
Gerrit Schoettler
Ashvin Nair
J. A. Ojea
Sergey Levine
Eugen Solowjow
OffRLOnRL
70
87
0
29 Apr 2020
Efficient Black-Box Planning Using Macro-Actions with Focused Effects
Efficient Black-Box Planning Using Macro-Actions with Focused Effects
Cameron Allen
Michael Katz
Tim Klinger
George Konidaris
Matthew D Riemer
Gerald Tesauro
48
9
0
28 Apr 2020
Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic
  Reinforcement Learning
Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning
Ryan Julian
Benjamin Swanson
Gaurav Sukhatme
Sergey Levine
Chelsea Finn
Karol Hausman
OnRLCLL
92
43
0
21 Apr 2020
Shortcut Learning in Deep Neural Networks
Shortcut Learning in Deep Neural Networks
Robert Geirhos
J. Jacobsen
Claudio Michaelis
R. Zemel
Wieland Brendel
Matthias Bethge
Felix Wichmann
231
2,074
0
16 Apr 2020
State-Only Imitation Learning for Dexterous Manipulation
State-Only Imitation Learning for Dexterous Manipulation
Ilija Radosavovic
Xiaolong Wang
Lerrel Pinto
Jitendra Malik
OffRL
94
123
0
07 Apr 2020
Trying AGAIN instead of Trying Longer: Prior Learning for Automatic
  Curriculum Learning
Trying AGAIN instead of Trying Longer: Prior Learning for Automatic Curriculum Learning
Rémy Portelas
Katja Hofmann
Pierre-Yves Oudeyer
23
1
0
07 Apr 2020
Robust Deep Reinforcement Learning against Adversarial Perturbations on
  State Observations
Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations
Huan Zhang
Hongge Chen
Chaowei Xiao
Yue Liu
Mingyan D. Liu
Duane S. Boning
Cho-Jui Hsieh
AAML
176
276
0
19 Mar 2020
Learning to Fly via Deep Model-Based Reinforcement Learning
Learning to Fly via Deep Model-Based Reinforcement Learning
Philip Becker-Ehmck
Maximilian Karl
Jan Peters
Patrick van der Smagt
SSL
132
37
0
19 Mar 2020
Automatic Curriculum Learning For Deep RL: A Short Survey
Automatic Curriculum Learning For Deep RL: A Short Survey
Rémy Portelas
Cédric Colas
Lilian Weng
Katja Hofmann
Pierre-Yves Oudeyer
ODL
119
176
0
10 Mar 2020
Deep Adversarial Reinforcement Learning for Object Disentangling
Deep Adversarial Reinforcement Learning for Object Disentangling
Melvin Laux
Oleg Arenz
Jan Peters
Joni Pajarinen
DRL
48
3
0
08 Mar 2020
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