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Variational Information Maximisation for Intrinsically Motivated
  Reinforcement Learning

Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning

29 September 2015
S. Mohamed
Danilo Jimenez Rezende
    DRLSSL
ArXiv (abs)PDFHTML

Papers citing "Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning"

50 / 157 papers shown
Title
Invariant Information Bottleneck for Domain Generalization
Invariant Information Bottleneck for Domain Generalization
Yue Liu
Yifei Shen
Yezhen Wang
Wenzhen Zhu
Colorado Reed
Jun Zhang
Dongsheng Li
Kurt Keutzer
Han Zhao
OOD
97
117
0
11 Jun 2021
Exploration and preference satisfaction trade-off in reward-free
  learning
Exploration and preference satisfaction trade-off in reward-free learning
Noor Sajid
P. Tigas
Alexey Zakharov
Zafeirios Fountas
Karl J. Friston
84
20
0
08 Jun 2021
Causal Influence Detection for Improving Efficiency in Reinforcement
  Learning
Causal Influence Detection for Improving Efficiency in Reinforcement Learning
Maximilian Seitzer
Bernhard Schölkopf
Georg Martius
CML
109
78
0
07 Jun 2021
Variational Empowerment as Representation Learning for Goal-Based
  Reinforcement Learning
Variational Empowerment as Representation Learning for Goal-Based Reinforcement Learning
Jongwook Choi
Archit Sharma
Honglak Lee
Sergey Levine
S. Gu
DRL
67
21
0
02 Jun 2021
Did I do that? Blame as a means to identify controlled effects in
  reinforcement learning
Did I do that? Blame as a means to identify controlled effects in reinforcement learning
Oriol Corcoll
Youssef Mohamed
Raul Vicente
58
3
0
01 Jun 2021
Understanding the Origin of Information-Seeking Exploration in
  Probabilistic Objectives for Control
Understanding the Origin of Information-Seeking Exploration in Probabilistic Objectives for Control
Beren Millidge
A. Seth
Christopher L. Buckley
122
12
0
11 Mar 2021
Behavior From the Void: Unsupervised Active Pre-Training
Behavior From the Void: Unsupervised Active Pre-Training
Hao Liu
Pieter Abbeel
VLMSSL
131
207
0
08 Mar 2021
Task-Agnostic Morphology Evolution
Task-Agnostic Morphology Evolution
D. Hejna
Pieter Abbeel
Lerrel Pinto
74
27
0
25 Feb 2021
Beyond Fine-Tuning: Transferring Behavior in Reinforcement Learning
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
OffRLOnRL
83
26
0
24 Feb 2021
Towards Continual Reinforcement Learning: A Review and Perspectives
Towards Continual Reinforcement Learning: A Review and Perspectives
Khimya Khetarpal
Matthew D Riemer
Irina Rish
Doina Precup
CLLOffRL
142
324
0
25 Dec 2020
Autotelic Agents with Intrinsically Motivated Goal-Conditioned
  Reinforcement Learning: a Short Survey
Autotelic Agents with Intrinsically Motivated Goal-Conditioned Reinforcement Learning: a Short Survey
Cédric Colas
Tristan Karch
Olivier Sigaud
Pierre-Yves Oudeyer
154
95
0
17 Dec 2020
BeBold: Exploration Beyond the Boundary of Explored Regions
BeBold: Exploration Beyond the Boundary of Explored Regions
Tianjun Zhang
Huazhe Xu
Xiaolong Wang
Yi Wu
Kurt Keutzer
Joseph E. Gonzalez
Yuandong Tian
81
40
0
15 Dec 2020
Relative Variational Intrinsic Control
Relative Variational Intrinsic Control
Kate Baumli
David Warde-Farley
Steven Hansen
Volodymyr Mnih
79
43
0
14 Dec 2020
Continual Learning of Control Primitives: Skill Discovery via
  Reset-Games
Continual Learning of Control Primitives: Skill Discovery via Reset-Games
Kelvin Xu
Siddharth Verma
Chelsea Finn
Sergey Levine
CLL
83
34
0
10 Nov 2020
Behavior Priors for Efficient Reinforcement Learning
Behavior Priors for Efficient Reinforcement Learning
Dhruva Tirumala
Alexandre Galashov
Hyeonwoo Noh
Leonard Hasenclever
Razvan Pascanu
...
Guillaume Desjardins
Wojciech M. Czarnecki
Arun Ahuja
Yee Whye Teh
N. Heess
114
40
0
27 Oct 2020
An Empowerment-based Solution to Robotic Manipulation Tasks with Sparse
  Rewards
An Empowerment-based Solution to Robotic Manipulation Tasks with Sparse Rewards
Siyu Dai
Wenyuan Xu
Andreas G. Hofmann
B. Williams
97
8
0
15 Oct 2020
Variational Intrinsic Control Revisited
Variational Intrinsic Control Revisited
Taehwan Kwon
31
12
0
07 Oct 2020
Novelty Search in Representational Space for Sample Efficient
  Exploration
Novelty Search in Representational Space for Sample Efficient Exploration
Ruo Yu Tao
Vincent François-Lavet
Joelle Pineau
90
45
0
28 Sep 2020
Action and Perception as Divergence Minimization
Action and Perception as Divergence Minimization
Danijar Hafner
Pedro A. Ortega
Jimmy Ba
Thomas Parr
Karl J. Friston
N. Heess
91
53
0
03 Sep 2020
Instance-Aware Graph Convolutional Network for Multi-Label
  Classification
Instance-Aware Graph Convolutional Network for Multi-Label Classification
Yun Wang
Tong Zhang
Zhen Cui
Chunyan Xu
Jian Yang
GNN
41
4
0
19 Aug 2020
Efficient Empowerment Estimation for Unsupervised Stabilization
Efficient Empowerment Estimation for Unsupervised Stabilization
Ruihan Zhao
Kevin Lu
Pieter Abbeel
Stas Tiomkin
58
8
0
14 Jul 2020
Explore and Explain: Self-supervised Navigation and Recounting
Explore and Explain: Self-supervised Navigation and Recounting
Roberto Bigazzi
Federico Landi
Marcella Cornia
S. Cascianelli
Lorenzo Baraldi
Rita Cucchiara
EgoVLM&Ro
78
17
0
14 Jul 2020
Task-Agnostic Exploration via Policy Gradient of a Non-Parametric State
  Entropy Estimate
Task-Agnostic Exploration via Policy Gradient of a Non-Parametric State Entropy Estimate
Mirco Mutti
Lorenzo Pratissoli
Marcello Restelli
73
19
0
09 Jul 2020
End-Effect Exploration Drive for Effective Motor Learning
End-Effect Exploration Drive for Effective Motor Learning
Emmanuel Daucé
17
1
0
29 Jun 2020
AvE: Assistance via Empowerment
AvE: Assistance via Empowerment
Yuqing Du
Stas Tiomkin
Emre Kıcıman
Daniel Polani
Pieter Abbeel
Anca Dragan
113
35
0
26 Jun 2020
Deep Reinforcement and InfoMax Learning
Deep Reinforcement and InfoMax Learning
Bogdan Mazoure
Rémi Tachet des Combes
T. Doan
Philip Bachman
R. Devon Hjelm
AI4CE
82
109
0
12 Jun 2020
From proprioception to long-horizon planning in novel environments: A
  hierarchical RL model
From proprioception to long-horizon planning in novel environments: A hierarchical RL model
Nishad Gothoskar
Miguel Lázaro-Gredilla
Dileep George
33
0
0
11 Jun 2020
Adaptive Reward-Free Exploration
Adaptive Reward-Free Exploration
E. Kaufmann
Pierre Ménard
O. D. Domingues
Anders Jonsson
Edouard Leurent
Michal Valko
77
82
0
11 Jun 2020
Exploration by Maximizing Rényi Entropy for Reward-Free RL Framework
Exploration by Maximizing Rényi Entropy for Reward-Free RL Framework
Wei Shen
Yuanying Cai
Longbo Huang
Jian Li
OffRL
37
1
0
11 Jun 2020
Gradient Monitored Reinforcement Learning
Gradient Monitored Reinforcement Learning
Mohammed Sharafath Abdul Hameed
Gavneet Singh Chadha
Andreas Schwung
S. Ding
97
11
0
25 May 2020
Simple Sensor Intentions for Exploration
Simple Sensor Intentions for Exploration
Tim Hertweck
Martin Riedmiller
Michael Bloesch
Jost Tobias Springenberg
Noah Y. Siegel
Markus Wulfmeier
Roland Hafner
N. Heess
68
10
0
15 May 2020
Progressive growing of self-organized hierarchical representations for
  exploration
Progressive growing of self-organized hierarchical representations for exploration
Mayalen Etcheverry
Pierre-Yves Oudeyer
Chris Reinke
52
0
0
13 May 2020
Planning to Explore via Self-Supervised World Models
Planning to Explore via Self-Supervised World Models
Ramanan Sekar
Oleh Rybkin
Kostas Daniilidis
Pieter Abbeel
Danijar Hafner
Deepak Pathak
SSL
115
412
0
12 May 2020
Maximizing Information Gain in Partially Observable Environments via
  Prediction Reward
Maximizing Information Gain in Partially Observable Environments via Prediction Reward
Yash Satsangi
Sungsu Lim
Shimon Whiteson
F. Oliehoek
Martha White
80
15
0
11 May 2020
Emergent Real-World Robotic Skills via Unsupervised Off-Policy
  Reinforcement Learning
Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning
Archit Sharma
Michael Ahn
Sergey Levine
Vikash Kumar
Karol Hausman
S. Gu
SSLOffRL
54
47
0
27 Apr 2020
The Variational Bandwidth Bottleneck: Stochastic Evaluation on an
  Information Budget
The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget
Anirudh Goyal
Yoshua Bengio
M. Botvinick
Sergey Levine
70
24
0
24 Apr 2020
Whence the Expected Free Energy?
Whence the Expected Free Energy?
Beren Millidge
Alexander Tschantz
Christopher L. Buckley
76
70
0
17 Apr 2020
Social Navigation with Human Empowerment driven Deep Reinforcement
  Learning
Social Navigation with Human Empowerment driven Deep Reinforcement Learning
T. V. D. Heiden
Christian Weiss
H. V. Hoof
59
13
0
18 Mar 2020
Option Discovery in the Absence of Rewards with Manifold Analysis
Option Discovery in the Absence of Rewards with Manifold Analysis
Amitay Bar
Ronen Talmon
Ron Meir
69
5
0
12 Mar 2020
Reinforcement Learning through Active Inference
Reinforcement Learning through Active Inference
Alexander Tschantz
Beren Millidge
A. Seth
Christopher L. Buckley
AI4CE
81
72
0
28 Feb 2020
Explore, Discover and Learn: Unsupervised Discovery of State-Covering
  Skills
Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills
Victor Campos
Alexander R. Trott
Caiming Xiong
R. Socher
Xavier Giró-i-Nieto
Jordi Torres
OffRL
101
156
0
10 Feb 2020
Ready Policy One: World Building Through Active Learning
Ready Policy One: World Building Through Active Learning
Philip J. Ball
Jack Parker-Holder
Aldo Pacchiano
K. Choromanski
Stephen J. Roberts
OffRL
92
49
0
07 Feb 2020
Learning to Reach Goals via Iterated Supervised Learning
Learning to Reach Goals via Iterated Supervised Learning
Dibya Ghosh
Abhishek Gupta
Ashwin Reddy
Justin Fu
Coline Devin
Benjamin Eysenbach
Sergey Levine
117
35
0
12 Dec 2019
SMiRL: Surprise Minimizing Reinforcement Learning in Unstable
  Environments
SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments
Glen Berseth
Daniel Geng
Coline Devin
Nicholas Rhinehart
Chelsea Finn
Dinesh Jayaraman
Sergey Levine
96
22
0
11 Dec 2019
Unsupervised Curricula for Visual Meta-Reinforcement Learning
Unsupervised Curricula for Visual Meta-Reinforcement Learning
Allan Jabri
Kyle Hsu
Benjamin Eysenbach
Abhishek Gupta
Sergey Levine
Chelsea Finn
VLMOODSSLOffRL
82
65
0
09 Dec 2019
Reinforcement Learning-based Visual Navigation with
  Information-Theoretic Regularization
Reinforcement Learning-based Visual Navigation with Information-Theoretic Regularization
Qiaoyun Wu
Kai Xu
Jun Wang
Mingliang Xu
Xiaoxi Gong
Tianyi Zhou
87
30
0
09 Dec 2019
Learning Efficient Representation for Intrinsic Motivation
Learning Efficient Representation for Intrinsic Motivation
Ruihan Zhao
Stas Tiomkin
Pieter Abbeel
56
5
0
04 Dec 2019
Learning Likelihoods with Conditional Normalizing Flows
Learning Likelihoods with Conditional Normalizing Flows
Christina Winkler
Daniel E. Worrall
Emiel Hoogeboom
Max Welling
TPM
280
227
0
29 Nov 2019
Scaling active inference
Scaling active inference
Alexander Tschantz
Manuel Baltieri
A. Seth
Christopher L. Buckley
BDLAI4CE
68
69
0
24 Nov 2019
Implicit Generative Modeling for Efficient Exploration
Implicit Generative Modeling for Efficient Exploration
Neale Ratzlaff
Qinxun Bai
Fuxin Li
Wenyuan Xu
70
12
0
19 Nov 2019
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