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1704.03012
Cited By
Stochastic Neural Networks for Hierarchical Reinforcement Learning
10 April 2017
Carlos Florensa
Yan Duan
Pieter Abbeel
BDL
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Papers citing
"Stochastic Neural Networks for Hierarchical Reinforcement Learning"
50 / 221 papers shown
AMP: Adversarial Motion Priors for Stylized Physics-Based Character Control
ACM Transactions on Graphics (TOG), 2021
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Ze Ma
Pieter Abbeel
Sergey Levine
Angjoo Kanazawa
179
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05 Apr 2021
Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning
International Conference on Machine Learning (ICML), 2021
Hiroki Furuta
T. Matsushima
Tadashi Kozuno
Y. Matsuo
Sergey Levine
Ofir Nachum
S. Gu
OffRL
152
16
0
23 Mar 2021
Online Baum-Welch algorithm for Hierarchical Imitation Learning
IEEE Conference on Decision and Control (CDC), 2021
Vittorio Giammarino
I. Paschalidis
OffRL
149
5
0
22 Mar 2021
Solving Compositional Reinforcement Learning Problems via Task Reduction
International Conference on Learning Representations (ICLR), 2021
Yunfei Li
Yilin Wu
Huazhe Xu
Xiaolong Wang
Yi Wu
199
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0
13 Mar 2021
Discovering Diverse Solutions in Deep Reinforcement Learning by Maximizing State-Action-Based Mutual Information
Neural Networks (NN), 2021
Takayuki Osa
Voot Tangkaratt
Masashi Sugiyama
298
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12 Mar 2021
Beyond Fine-Tuning: Transferring Behavior in Reinforcement Learning
Victor Campos
Pablo Sprechmann
Steven Hansen
André Barreto
Steven Kapturowski
Alex Vitvitskyi
Adria Puigdomenech Badia
Charles Blundell
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319
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24 Feb 2021
Diverse Auto-Curriculum is Critical for Successful Real-World Multiagent Learning Systems
Adaptive Agents and Multi-Agent Systems (AAMAS), 2021
Yaodong Yang
Jun Luo
Ying Wen
Oliver Slumbers
D. Graves
H. Ammar
Jun Wang
Matthew E. Taylor
175
39
0
15 Feb 2021
State-Aware Variational Thompson Sampling for Deep Q-Networks
Adaptive Agents and Multi-Agent Systems (AAMAS), 2021
Siddharth Aravindan
W. Lee
200
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0
07 Feb 2021
Hierarchical Reinforcement Learning By Discovering Intrinsic Options
International Conference on Learning Representations (ICLR), 2021
Jesse Zhang
Haonan Yu
Wenyuan Xu
BDL
410
95
0
16 Jan 2021
Continuous Transition: Improving Sample Efficiency for Continuous Control Problems via MixUp
IEEE International Conference on Robotics and Automation (ICRA), 2020
Junfan Lin
Zhongzhan Huang
Keze Wang
Xiaodan Liang
Weiwei Chen
Liang Lin
170
12
0
30 Nov 2020
Latent Skill Planning for Exploration and Transfer
International Conference on Learning Representations (ICLR), 2020
Kevin Xie
Homanga Bharadhwaj
Danijar Hafner
Animesh Garg
Florian Shkurti
281
24
0
27 Nov 2020
From Pixels to Legs: Hierarchical Learning of Quadruped Locomotion
Conference on Robot Learning (CoRL), 2020
Deepali Jain
Atil Iscen
Ken Caluwaerts
210
36
0
23 Nov 2020
Parrot: Data-Driven Behavioral Priors for Reinforcement Learning
International Conference on Learning Representations (ICLR), 2020
Avi Singh
Huihan Liu
G. Zhou
Albert Yu
Nicholas Rhinehart
Sergey Levine
OffRL
OnRL
258
159
0
19 Nov 2020
Distilling a Hierarchical Policy for Planning and Control via Representation and Reinforcement Learning
IEEE International Conference on Robotics and Automation (ICRA), 2020
Jung-Su Ha
Young-Jin Park
Hyeok-Joo Chae
Soon-Seo Park
Han-Lim Choi
264
3
0
16 Nov 2020
Continual Learning of Control Primitives: Skill Discovery via Reset-Games
Kelvin Xu
Siddharth Verma
Chelsea Finn
Sergey Levine
CLL
199
34
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10 Nov 2020
Harnessing Distribution Ratio Estimators for Learning Agents with Quality and Diversity
Tanmay Gangwani
Jian Peng
Yuanshuo Zhou
184
12
0
05 Nov 2020
Ask Your Humans: Using Human Instructions to Improve Generalization in Reinforcement Learning
International Conference on Learning Representations (ICLR), 2020
Valerie Chen
Abhinav Gupta
Kenneth Marino
OffRL
375
44
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01 Nov 2020
Behavior Priors for Efficient Reinforcement Learning
Journal of machine learning research (JMLR), 2020
Dhruva Tirumala
Alexandre Galashov
Hyeonwoo Noh
Leonard Hasenclever
Razvan Pascanu
...
Guillaume Desjardins
Wojciech M. Czarnecki
Arun Ahuja
Yee Whye Teh
N. Heess
242
46
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27 Oct 2020
Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness
Long Zhao
Ting Liu
Xi Peng
Dimitris N. Metaxas
OOD
AAML
429
184
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15 Oct 2020
Temporal Difference Uncertainties as a Signal for Exploration
Sebastian Flennerhag
Jane X. Wang
Pablo Sprechmann
Francesco Visin
Alexandre Galashov
Steven Kapturowski
Diana Borsa
N. Heess
André Barreto
Razvan Pascanu
OffRL
206
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05 Oct 2020
Disentangling causal effects for hierarchical reinforcement learning
Oriol Corcoll
Raul Vicente
CML
222
11
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03 Oct 2020
Physically Embedded Planning Problems: New Challenges for Reinforcement Learning
M. Berk Mirza
Andrew Jaegle
Jonathan J. Hunt
A. Guez
S. Tunyasuvunakool
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Peter Karkus
S. Racanière
Lars Buesing
Timothy Lillicrap
N. Heess
AI4CE
157
13
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11 Sep 2020
Action and Perception as Divergence Minimization
Danijar Hafner
Pedro A. Ortega
Jimmy Ba
Thomas Parr
Karl J. Friston
N. Heess
291
60
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03 Sep 2020
OCEAN: Online Task Inference for Compositional Tasks with Context Adaptation
Hongyu Ren
Yuke Zhu
J. Leskovec
Anima Anandkumar
Animesh Garg
LRM
108
4
0
17 Aug 2020
A Development Cycle for Automated Self-Exploration of Robot Behaviors
AI Perspectives (AP), 2020
T. Roehr
Daniel Harnack
Hendrik Wöhrle
Felix Wiebe
M. Schilling
Oscar Lima
M. Langosz
Shivesh Kumar
S. Straube
Frank Kirchner
198
2
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29 Jul 2020
Learning the Solution Manifold in Optimization and Its Application in Motion Planning
Takayuki Osa
136
2
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24 Jul 2020
Model-based Reinforcement Learning: A Survey
Thomas M. Moerland
Joost Broekens
Aske Plaat
Catholijn M. Jonker
OffRL
493
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30 Jun 2020
ELSIM: End-to-end learning of reusable skills through intrinsic motivation
A. Aubret
L. Matignon
S. Hassas
93
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23 Jun 2020
CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information
Pengyu Cheng
Weituo Hao
Shuyang Dai
Jiachang Liu
Zhe Gan
Lawrence Carin
VLM
480
459
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22 Jun 2020
Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement Learning
Tianren Zhang
Shangqi Guo
Tian Tan
Xiaolin Hu
Feng Chen
423
98
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20 Jun 2020
From proprioception to long-horizon planning in novel environments: A hierarchical RL model
Nishad Gothoskar
Miguel Lázaro-Gredilla
Dileep George
110
0
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11 Jun 2020
Continuous Action Reinforcement Learning from a Mixture of Interpretable Experts
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020
R. Akrour
Davide Tateo
Jan Peters
199
26
0
10 Jun 2020
Guided Uncertainty-Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learning
Michelle A. Lee
Carlos Florensa
Jonathan Tremblay
Nathan D. Ratliff
Animesh Garg
Fabio Ramos
Dieter Fox
289
67
0
21 May 2020
Novel Policy Seeking with Constrained Optimization
Hao Sun
Zhenghao Peng
Bo Dai
Jian Guo
Dahua Lin
Bolei Zhou
331
15
0
21 May 2020
DREAM Architecture: a Developmental Approach to Open-Ended Learning in Robotics
Stéphane Doncieux
Nicolas Bredèche
L. L. Goff
Benoît Girard
Alexandre Coninx
...
Natalia Díaz Rodríguez
David Filliat
Timothy M. Hospedales
A. E. Eiben
Richard J. Duro
199
19
0
13 May 2020
Hierarchical Reinforcement Learning for Automatic Disease Diagnosis
Cheng Zhong
Kangenbei Liao
Wei Chen
Qianlong Liu
Baolin Peng
Xuanjing Huang
J. Peng
Zhongyu Wei
OffRL
111
5
0
29 Apr 2020
Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning
Archit Sharma
Michael Ahn
Sergey Levine
Vikash Kumar
Karol Hausman
S. Gu
SSL
OffRL
130
54
0
27 Apr 2020
Learning to Generalize Across Long-Horizon Tasks from Human Demonstrations
Ajay Mandlekar
Danfei Xu
Roberto Martín-Martín
Silvio Savarese
Li Fei-Fei
OffRL
331
165
0
13 Mar 2020
Option Discovery in the Absence of Rewards with Manifold Analysis
International Conference on Machine Learning (ICML), 2020
Amitay Bar
Ronen Talmon
Ron Meir
134
6
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12 Mar 2020
Meta-learning curiosity algorithms
International Conference on Learning Representations (ICLR), 2020
Ferran Alet
Martin Schneider
Tomas Lozano-Perez
L. Kaelbling
243
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11 Mar 2020
Hierarchically Decoupled Imitation for Morphological Transfer
International Conference on Machine Learning (ICML), 2020
D. Hejna
Pieter Abbeel
Lerrel Pinto
LM&Ro
154
44
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03 Mar 2020
Generalized Hindsight for Reinforcement Learning
Neural Information Processing Systems (NeurIPS), 2020
Alexander C. Li
Lerrel Pinto
Pieter Abbeel
163
76
0
26 Feb 2020
Learning Functionally Decomposed Hierarchies for Continuous Control Tasks with Path Planning
IEEE Robotics and Automation Letters (RA-L), 2020
Sammy Christen
Lukás Jendele
Emre Aksan
Otmar Hilliges
OffRL
205
29
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14 Feb 2020
Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills
International Conference on Machine Learning (ICML), 2020
Victor Campos
Alexander R. Trott
Caiming Xiong
R. Socher
Xavier Giró-i-Nieto
Jordi Torres
OffRL
483
168
0
10 Feb 2020
Temporal-adaptive Hierarchical Reinforcement Learning
Wen-Ji Zhou
Yang Yu
108
4
0
06 Feb 2020
Inter-Level Cooperation in Hierarchical Reinforcement Learning
Abdul Rahman Kreidieh
Yiling You
Nathan Lichtlé
Samyak Parajuli
Rayyan Nasr
Alexandre M. Bayen
277
16
0
05 Dec 2019
Unsupervised Reinforcement Learning of Transferable Meta-Skills for Embodied Navigation
Computer Vision and Pattern Recognition (CVPR), 2019
Juncheng Li
Xinze Wang
Siliang Tang
Haizhou Shi
Leilei Gan
Yueting Zhuang
William Yang Wang
SSL
327
79
0
18 Nov 2019
Learning from Trajectories via Subgoal Discovery
Neural Information Processing Systems (NeurIPS), 2019
S. Paul
J. Baar
Amit K. Roy-Chowdhury
257
49
0
03 Nov 2019
MAVEN: Multi-Agent Variational Exploration
Neural Information Processing Systems (NeurIPS), 2019
Anuj Mahajan
Tabish Rashid
Mikayel Samvelyan
Shimon Whiteson
DRL
422
408
0
16 Oct 2019
Influence-Based Multi-Agent Exploration
International Conference on Learning Representations (ICLR), 2019
Tonghan Wang
Jianhao Wang
Yi Wu
Chongjie Zhang
195
150
0
12 Oct 2019
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