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1611.07507
Cited By
Variational Intrinsic Control
22 November 2016
Karol Gregor
Danilo Jimenez Rezende
Daan Wierstra
DRL
OffRL
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Papers citing
"Variational Intrinsic Control"
50 / 311 papers shown
CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery
Michael Laskin
Hao Liu
Xue Bin Peng
Denis Yarats
Aravind Rajeswaran
Pieter Abbeel
SSL
483
76
0
01 Feb 2022
State-Conditioned Adversarial Subgoal Generation
AAAI Conference on Artificial Intelligence (AAAI), 2022
V. Wang
Joni Pajarinen
Tinghuai Wang
Joni-Kristian Kämäräinen
294
15
0
24 Jan 2022
Solving Dynamic Principal-Agent Problems with a Rationally Inattentive Principal
Tong Mu
Stephan Zheng
Alexander R. Trott
169
3
0
18 Jan 2022
Physical Derivatives: Computing policy gradients by physical forward-propagation
Arash Mehrjou
Ashkan Soleymani
Stefan Bauer
Bernhard Schölkopf
165
0
0
15 Jan 2022
Constructing a Good Behavior Basis for Transfer using Generalized Policy Updates
International Conference on Learning Representations (ICLR), 2021
Safa Alver
Doina Precup
OffRL
276
17
0
30 Dec 2021
Autonomous Reinforcement Learning: Formalism and Benchmarking
International Conference on Learning Representations (ICLR), 2021
Archit Sharma
Kelvin Xu
Nikhil Sardana
Abhishek Gupta
Karol Hausman
Sergey Levine
Chelsea Finn
OffRL
232
34
0
17 Dec 2021
Unsupervised Reinforcement Learning in Multiple Environments
Mirco Mutti
Mattia Mancassola
Marcello Restelli
OffRL
155
27
0
16 Dec 2021
Learning Transferable Motor Skills with Hierarchical Latent Mixture Policies
Dushyant Rao
Fereshteh Sadeghi
Leonard Hasenclever
Markus Wulfmeier
Martina Zambelli
...
Dhruva Tirumala
Y. Aytar
J. Merel
N. Heess
R. Hadsell
238
33
0
09 Dec 2021
Information is Power: Intrinsic Control via Information Capture
Nick Rhinehart
Jenny Wang
Glen Berseth
John D. Co-Reyes
Danijar Hafner
Chelsea Finn
Sergey Levine
182
10
0
07 Dec 2021
Flexible Option Learning
Neural Information Processing Systems (NeurIPS), 2021
Martin Klissarov
Doina Precup
OffRL
177
31
0
06 Dec 2021
Wasserstein Distance Maximizing Intrinsic Control
Ishan Durugkar
Steven Hansen
Stephen Spencer
Volodymyr Mnih
161
6
0
28 Oct 2021
From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence
Nicholas Roy
Ingmar Posner
Timothy D. Barfoot
Philippe Beaudoin
Yoshua Bengio
...
S. Schaal
Gaurav Sukhatme
D. Thérien
Marc Toussaint
M. van de Panne
318
84
0
28 Oct 2021
URLB: Unsupervised Reinforcement Learning Benchmark
Michael Laskin
Denis Yarats
Hao Liu
Kimin Lee
Albert Zhan
Kevin Lu
Catherine Cang
Lerrel Pinto
Pieter Abbeel
SSL
OffRL
234
161
0
28 Oct 2021
TRAIL: Near-Optimal Imitation Learning with Suboptimal Data
International Conference on Learning Representations (ICLR), 2021
Mengjiao Yang
Sergey Levine
Ofir Nachum
OffRL
202
50
0
27 Oct 2021
Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching
Pierre-Alexandre Kamienny
Jean Tarbouriech
Sylvain Lamprier
A. Lazaric
Ludovic Denoyer
SSL
356
21
0
27 Oct 2021
Towards Robust Bisimulation Metric Learning
Mete Kemertas
Tristan Aumentado-Armstrong
OffRL
194
57
0
27 Oct 2021
Average-Reward Learning and Planning with Options
Yi Wan
A. Naik
R. Sutton
90
10
0
26 Oct 2021
Understanding the World Through Action
Conference on Robot Learning (CoRL), 2021
Sergey Levine
SSL
OffRL
149
26
0
24 Oct 2021
Anti-Concentrated Confidence Bonuses for Scalable Exploration
International Conference on Learning Representations (ICLR), 2021
Jordan T. Ash
Cyril Zhang
Surbhi Goel
A. Krishnamurthy
Sham Kakade
255
8
0
21 Oct 2021
Hierarchical Skills for Efficient Exploration
Neural Information Processing Systems (NeurIPS), 2021
Jonas Gehring
Gabriel Synnaeve
Andreas Krause
Nicolas Usunier
233
47
0
20 Oct 2021
Discovering and Achieving Goals via World Models
Russell Mendonca
Oleh Rybkin
Kostas Daniilidis
Danijar Hafner
Deepak Pathak
290
159
0
18 Oct 2021
Provable RL with Exogenous Distractors via Multistep Inverse Dynamics
Yonathan Efroni
Dipendra Kumar Misra
A. Krishnamurthy
Alekh Agarwal
John Langford
OffRL
205
24
0
17 Oct 2021
Wasserstein Unsupervised Reinforcement Learning
Shuncheng He
Yuhang Jiang
Hongchang Zhang
Jianzhun Shao
Xiangyang Ji
OffRL
220
28
0
15 Oct 2021
Temporal Abstraction in Reinforcement Learning with the Successor Representation
Journal of machine learning research (JMLR), 2021
Marlos C. Machado
André Barreto
Doina Precup
Michael Bowling
317
56
0
12 Oct 2021
Braxlines: Fast and Interactive Toolkit for RL-driven Behavior Engineering beyond Reward Maximization
S. Gu
Manfred Diaz
Daniel Freeman
Hiroki Furuta
Seyed Kamyar Seyed Ghasemipour
Anton Raichuk
Byron David
Erik Frey
Erwin Coumans
Olivier Bachem
140
15
0
10 Oct 2021
Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity
Adaptive Agents and Multi-Agent Systems (AAMAS), 2021
M. Garnelo
Wojciech M. Czarnecki
Siqi Liu
Dhruva Tirumala
Junhyuk Oh
Gauthier Gidel
H. V. Hasselt
David Balduzzi
225
25
0
08 Oct 2021
The Information Geometry of Unsupervised Reinforcement Learning
Benjamin Eysenbach
Ruslan Salakhutdinov
Sergey Levine
SSL
OffRL
271
38
0
06 Oct 2021
A First-Occupancy Representation for Reinforcement Learning
Theodore H. Moskovitz
S. Wilson
M. Sahani
274
16
0
28 Sep 2021
Bottom-Up Skill Discovery from Unsegmented Demonstrations for Long-Horizon Robot Manipulation
Yifeng Zhu
Peter Stone
Yuke Zhu
366
93
0
28 Sep 2021
Is Curiosity All You Need? On the Utility of Emergent Behaviours from Curious Exploration
Oliver Groth
Markus Wulfmeier
Giulia Vezzani
Vibhavari Dasagi
Tim Hertweck
Agrim Gupta
N. Heess
Martin Riedmiller
LRM
224
21
0
17 Sep 2021
Dynamics-Aware Quality-Diversity for Efficient Learning of Skill Repertoires
Bryan Lim
Luca Grillotti
Lorenzo Bernasconi
Antoine Cully
176
28
0
16 Sep 2021
Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain
Jianye Hao
Zhenxing Ge
Hongyao Tang
Chenjia Bai
Jinyi Liu
Zhaopeng Meng
Peng Liu
Zhen Wang
OffRL
376
154
0
14 Sep 2021
APS: Active Pretraining with Successor Features
International Conference on Machine Learning (ICML), 2021
Hao Liu
Pieter Abbeel
215
138
0
31 Aug 2021
When should agents explore?
International Conference on Learning Representations (ICLR), 2021
Miruna Pislar
David Szepesvari
Georg Ostrovski
Diana Borsa
Tom Schaul
189
26
0
26 Aug 2021
Collect & Infer -- a fresh look at data-efficient Reinforcement Learning
Conference on Robot Learning (CoRL), 2021
Martin Riedmiller
Jost Tobias Springenberg
Agrim Gupta
N. Heess
OffRL
171
21
0
23 Aug 2021
Co-GAIL: Learning Diverse Strategies for Human-Robot Collaboration
Conference on Robot Learning (CoRL), 2021
Chen Wang
Claudia Pérez-DÁrpino
Danfei Xu
Li Fei-Fei
Chenxi Liu
Silvio Savarese
323
41
0
13 Aug 2021
Learning Task Agnostic Skills with Data-driven Guidance
E. Klemsdal
Sverre Herland
Abdulmajid Murad
104
2
0
04 Aug 2021
Learning more skills through optimistic exploration
International Conference on Learning Representations (ICLR), 2021
D. Strouse
Kate Baumli
David Warde-Farley
Vlad Mnih
Steven Hansen
SSL
280
51
0
29 Jul 2021
Learning Altruistic Behaviours in Reinforcement Learning without External Rewards
International Conference on Learning Representations (ICLR), 2021
Tim Franzmeyer
Mateusz Malinowski
João F. Henriques
324
10
0
20 Jul 2021
Unsupervised Skill-Discovery and Skill-Learning in Minecraft
J. J. Nieto
Roger Creus
Xavier Giró-i-Nieto
SSL
DRL
165
5
0
18 Jul 2021
Experimental Evidence that Empowerment May Drive Exploration in Sparse-Reward Environments
International Conference on Development and Learning (ICDL), 2021
F. Massari
Martin Biehl
L. Meeden
Ryota Kanai
116
0
0
14 Jul 2021
Explore and Control with Adversarial Surprise
Arnaud Fickinger
Natasha Jaques
Samyak Parajuli
Michael Chang
Nicholas Rhinehart
Glen Berseth
Stuart J. Russell
Sergey Levine
243
8
0
12 Jul 2021
Learning Task Informed Abstractions
International Conference on Machine Learning (ICML), 2021
Xiang Fu
Ge Yang
Pulkit Agrawal
Tommi Jaakkola
292
74
0
29 Jun 2021
Unsupervised Skill Discovery with Bottleneck Option Learning
International Conference on Machine Learning (ICML), 2021
Jaekyeom Kim
Seohong Park
Gunhee Kim
209
38
0
27 Jun 2021
Discovering Generalizable Skills via Automated Generation of Diverse Tasks
Kuan Fang
Yuke Zhu
Silvio Savarese
Li Fei-Fei
187
8
0
26 Jun 2021
MADE: Exploration via Maximizing Deviation from Explored Regions
Neural Information Processing Systems (NeurIPS), 2021
Tianjun Zhang
Paria Rashidinejad
Jiantao Jiao
Yuandong Tian
Joseph E. Gonzalez
Stuart J. Russell
OffRL
226
47
0
18 Jun 2021
Which Mutual-Information Representation Learning Objectives are Sufficient for Control?
Neural Information Processing Systems (NeurIPS), 2021
Kate Rakelly
Abhishek Gupta
Carlos Florensa
Sergey Levine
SSL
208
41
0
14 Jun 2021
Learning Routines for Effective Off-Policy Reinforcement Learning
International Conference on Machine Learning (ICML), 2021
Edoardo Cetin
Oya Celiktutan
113
1
0
05 Jun 2021
Variational Empowerment as Representation Learning for Goal-Based Reinforcement Learning
Jongwook Choi
Archit Sharma
Honglak Lee
Sergey Levine
S. Gu
DRL
211
23
0
02 Jun 2021
Discovering Diverse Nearly Optimal Policies with Successor Features
Tom Zahavy
Brendan O'Donoghue
André Barreto
Volodymyr Mnih
Sebastian Flennerhag
Satinder Singh
177
24
0
01 Jun 2021
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