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1812.07626
Cited By
Universal Successor Features Approximators
18 December 2018
Diana Borsa
André Barreto
John Quan
D. Mankowitz
Rémi Munos
H. V. Hasselt
David Silver
Tom Schaul
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Papers citing
"Universal Successor Features Approximators"
33 / 83 papers shown
Constructing a Good Behavior Basis for Transfer using Generalized Policy Updates
International Conference on Learning Representations (ICLR), 2021
Safa Alver
Doina Precup
OffRL
267
17
0
30 Dec 2021
Feature-Attending Recurrent Modules for Generalization in Reinforcement Learning
Wilka Carvalho
Andrew Kyle Lampinen
Kyriacos Nikiforou
Felix Hill
Murray Shanahan
OffRL
282
0
0
15 Dec 2021
Successor Feature Landmarks for Long-Horizon Goal-Conditioned Reinforcement Learning
Christopher Hoang
Sungryull Sohn
Jongwook Choi
Wilka Carvalho
Honglak Lee
192
38
0
18 Nov 2021
Successor Feature Neural Episodic Control
David Emukpere
Xavier Alameda-Pineda
Chris Reinke
BDL
190
3
0
04 Nov 2021
Successor Feature Representations
Chris Reinke
Xavier Alameda-Pineda
282
5
0
29 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
314
56
0
12 Oct 2021
APS: Active Pretraining with Successor Features
International Conference on Machine Learning (ICML), 2021
Hao Liu
Pieter Abbeel
211
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
184
26
0
26 Aug 2021
The Option Keyboard: Combining Skills in Reinforcement Learning
André Barreto
Diana Borsa
Shaobo Hou
Gheorghe Comanici
Eser Aygun
...
Daniel Toyama
Jonathan J. Hunt
Shibl Mourad
David Silver
Doina Precup
166
106
0
24 Jun 2021
DisTop: Discovering a Topological representation to learn diverse and rewarding skills
IEEE Transactions on Cognitive and Developmental Systems (IEEE TCDS), 2021
A. Aubret
L. Matignon
S. Hassas
187
12
0
06 Jun 2021
Risk-Aware Transfer in Reinforcement Learning using Successor Features
Neural Information Processing Systems (NeurIPS), 2021
Michael Gimelfarb
André Barreto
Scott Sanner
Chi-Guhn Lee
122
18
0
28 May 2021
DisCo RL: Distribution-Conditioned Reinforcement Learning for General-Purpose Policies
IEEE International Conference on Robotics and Automation (ICRA), 2021
Soroush Nasiriany
Vitchyr H. Pong
Ashvin Nair
Alexander Khazatsky
Glen Berseth
Sergey Levine
OffRL
290
15
0
23 Apr 2021
A Practical Guide to Multi-Objective Reinforcement Learning and Planning
Autonomous Agents and Multi-Agent Systems (AAMAS), 2021
Conor F. Hayes
Roxana Ruadulescu
Eugenio Bargiacchi
Johan Källström
Matthew Macfarlane
...
Ann Nowé
Gabriel de Oliveira Ramos
Marcello Restelli
Peter Vamplew
D. Roijers
OffRL
287
435
0
17 Mar 2021
Learning One Representation to Optimize All Rewards
Neural Information Processing Systems (NeurIPS), 2021
Ahmed Touati
Yann Ollivier
OffRL
338
85
0
14 Mar 2021
Successor Feature Sets: Generalizing Successor Representations Across Policies
AAAI Conference on Artificial Intelligence (AAAI), 2021
Kianté Brantley
Soroush Mehri
Geoffrey J. Gordon
OffRL
191
11
0
03 Mar 2021
PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning
International Conference on Machine Learning (ICML), 2021
Angelos Filos
Clare Lyle
Y. Gal
Sergey Levine
Natasha Jaques
Gregory Farquhar
194
27
0
24 Feb 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
OffRL
OnRL
306
29
0
24 Feb 2021
Return-Based Contrastive Representation Learning for Reinforcement Learning
International Conference on Learning Representations (ICLR), 2021
Guoqing Liu
Wei Shen
Li Zhao
Tao Qin
Jinhua Zhu
Jian Li
Nenghai Yu
Tie-Yan Liu
SSL
OffRL
266
52
0
22 Feb 2021
Autotelic Agents with Intrinsically Motivated Goal-Conditioned Reinforcement Learning: a Short Survey
Journal of Artificial Intelligence Research (JAIR), 2020
Cédric Colas
Tristan Karch
Olivier Sigaud
Pierre-Yves Oudeyer
844
120
0
17 Dec 2020
UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning
Tarun Gupta
Anuj Mahajan
Bei Peng
Wendelin Bohmer
Shimon Whiteson
OffRL
258
59
0
06 Oct 2020
Transfer Learning in Deep Reinforcement Learning: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020
Zhuangdi Zhu
Kaixiang Lin
Anil K. Jain
Jiayu Zhou
OffRL
LRM
658
790
0
16 Sep 2020
Rapid Task-Solving in Novel Environments
Samuel Ritter
Ryan Faulkner
Laurent Sartran
Adam Santoro
M. Botvinick
David Raposo
171
30
0
05 Jun 2020
The Value-Improvement Path: Towards Better Representations for Reinforcement Learning
AAAI Conference on Artificial Intelligence (AAAI), 2020
Will Dabney
André Barreto
Mark Rowland
Robert Dadashi
John Quan
Marc G. Bellemare
David Silver
265
71
0
03 Jun 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
478
167
0
10 Feb 2020
Adapting Behaviour for Learning Progress
Tom Schaul
Diana Borsa
David Ding
David Szepesvari
Georg Ostrovski
Will Dabney
Simon Osindero
239
20
0
14 Dec 2019
State2vec: Off-Policy Successor Features Approximators
Sephora Madjiheurem
Laura Toni
OOD
OffRL
105
5
0
22 Oct 2019
Universal Policies to Learn Them All
Hassam Sheikh
Ladislau Bölöni
OffRL
59
1
0
24 Aug 2019
VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation
Shamane Siriwardhana
Rivindu Weerasekera
Denys J. C. Matthies
Suranga Nanayakkara
83
8
0
18 Aug 2019
Better transfer learning with inferred successor maps
Neural Information Processing Systems (NeurIPS), 2019
T. Madarász
301
23
0
18 Jun 2019
Fast Task Inference with Variational Intrinsic Successor Features
International Conference on Learning Representations (ICLR), 2019
Steven Hansen
Will Dabney
André Barreto
T. Wiele
David Warde-Farley
Volodymyr Mnih
BDL
255
171
0
12 Jun 2019
Zero-shot task adaptation by homoiconic meta-mapping
Andrew Kyle Lampinen
James L. McClelland
244
1
0
23 May 2019
Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies
International Conference on Algorithmic Learning Theory (ALT), 2019
Tom Zahavy
Avinatan Hassidim
Haim Kaplan
Yishay Mansour
OffRL
151
7
0
26 Feb 2019
Dynamic Weights in Multi-Objective Deep Reinforcement Learning
Axel Abels
D. Roijers
Tom Lenaerts
A. Nowé
Denis Steckelmacher
OffRL
360
187
0
20 Sep 2018
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