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Learning Parsimonious Dynamics for Generalization in Reinforcement
  Learning

Learning Parsimonious Dynamics for Generalization in Reinforcement Learning

29 September 2022
Tankred Saanum
Eric Schulz
ArXiv (abs)PDFHTML

Papers citing "Learning Parsimonious Dynamics for Generalization in Reinforcement Learning"

21 / 21 papers shown
Title
Mastering Atari with Discrete World Models
Mastering Atari with Discrete World Models
Danijar Hafner
Timothy Lillicrap
Mohammad Norouzi
Jimmy Ba
DRL
111
861
0
05 Oct 2020
CURL: Contrastive Unsupervised Representations for Reinforcement
  Learning
CURL: Contrastive Unsupervised Representations for Reinforcement Learning
A. Srinivas
Michael Laskin
Pieter Abbeel
SSLDRLOffRL
91
1,091
0
08 Apr 2020
Decision-Making with Auto-Encoding Variational Bayes
Decision-Making with Auto-Encoding Variational Bayes
Romain Lopez
Pierre Boyeau
Nir Yosef
Michael I. Jordan
Jeffrey Regier
BDL
446
10,591
0
17 Feb 2020
Dream to Control: Learning Behaviors by Latent Imagination
Dream to Control: Learning Behaviors by Latent Imagination
Danijar Hafner
Timothy Lillicrap
Jimmy Ba
Mohammad Norouzi
VLM
124
1,371
0
03 Dec 2019
Soft Actor-Critic for Discrete Action Settings
Soft Actor-Critic for Discrete Action Settings
Petros Christodoulou
OffRL
141
299
0
16 Oct 2019
Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a
  Latent Variable Model
Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model
Alex X. Lee
Anusha Nagabandi
Pieter Abbeel
Sergey Levine
OffRLBDL
85
382
0
01 Jul 2019
Symmetry-Based Disentangled Representation Learning requires Interaction
  with Environments
Symmetry-Based Disentangled Representation Learning requires Interaction with Environments
Hugo Caselles-Dupré
Michael Garcia Ortiz
David Filliat
DRL
62
66
0
30 Mar 2019
Model-Based Reinforcement Learning for Atari
Model-Based Reinforcement Learning for Atari
Lukasz Kaiser
Mohammad Babaeizadeh
Piotr Milos
B. Osinski
R. Campbell
...
Sergey Levine
Afroz Mohiuddin
Ryan Sepassi
George Tucker
Henryk Michalewski
OffRL
132
866
0
01 Mar 2019
Towards a Definition of Disentangled Representations
Towards a Definition of Disentangled Representations
I. Higgins
David Amos
David Pfau
S. Racanière
Loic Matthey
Danilo Jimenez Rezende
Alexander Lerchner
OCLDRL
103
480
0
05 Dec 2018
A micro Lie theory for state estimation in robotics
A micro Lie theory for state estimation in robotics
J. Solà
Jeremie Deray
Dinesh Atchuthan
48
412
0
04 Dec 2018
Learning Latent Dynamics for Planning from Pixels
Learning Latent Dynamics for Planning from Pixels
Danijar Hafner
Timothy Lillicrap
Ian S. Fischer
Ruben Villegas
David R Ha
Honglak Lee
James Davidson
BDL
88
1,446
0
12 Nov 2018
Recurrent World Models Facilitate Policy Evolution
Recurrent World Models Facilitate Policy Evolution
David R Ha
Jürgen Schmidhuber
SyDaTPM
121
950
0
04 Sep 2018
Representation Learning with Contrastive Predictive Coding
Representation Learning with Contrastive Predictive Coding
Aaron van den Oord
Yazhe Li
Oriol Vinyals
DRLSSL
351
10,349
0
10 Jul 2018
Emergence of grid-like representations by training recurrent neural
  networks to perform spatial localization
Emergence of grid-like representations by training recurrent neural networks to perform spatial localization
Christopher J. Cueva
Xue-Xin Wei
48
216
0
21 Mar 2018
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement
  Learning with a Stochastic Actor
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
Tuomas Haarnoja
Aurick Zhou
Pieter Abbeel
Sergey Levine
314
8,396
0
04 Jan 2018
Neural Discrete Representation Learning
Neural Discrete Representation Learning
Aaron van den Oord
Oriol Vinyals
Koray Kavukcuoglu
BDLSSLOCL
228
5,061
0
02 Nov 2017
Learning to Navigate in Complex Environments
Learning to Navigate in Complex Environments
Piotr Wojciech Mirowski
Razvan Pascanu
Fabio Viola
Hubert Soyer
Andy Ballard
...
Ross Goroshin
Laurent Sifre
Koray Kavukcuoglu
D. Kumaran
R. Hadsell
107
880
0
11 Nov 2016
Embed to Control: A Locally Linear Latent Dynamics Model for Control
  from Raw Images
Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images
Manuel Watter
Jost Tobias Springenberg
Joschka Boedecker
Martin Riedmiller
BDL
82
847
0
24 Jun 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.9K
150,260
0
22 Dec 2014
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence
  Modeling
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
Junyoung Chung
Çağlar Gülçehre
Kyunghyun Cho
Yoshua Bengio
593
12,734
0
11 Dec 2014
Estimating or Propagating Gradients Through Stochastic Neurons for
  Conditional Computation
Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
Yoshua Bengio
Nicholas Léonard
Aaron Courville
384
3,151
0
15 Aug 2013
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