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Model-Based Reinforcement Learning for Atari
v1v2v3v4v5 (latest)

Model-Based Reinforcement Learning for Atari

1 March 2019
Lukasz Kaiser
Mohammad Babaeizadeh
Piotr Milos
B. Osinski
R. Campbell
K. Czechowski
D. Erhan
Chelsea Finn
Piotr Kozakowski
Sergey Levine
Afroz Mohiuddin
Ryan Sepassi
George Tucker
Henryk Michalewski
    OffRL
ArXiv (abs)PDFHTML

Papers citing "Model-Based Reinforcement Learning for Atari"

50 / 521 papers shown
Title
Explanation-Aware Experience Replay in Rule-Dense Environments
Explanation-Aware Experience Replay in Rule-Dense Environments
Francesco Sovrano
Alex Raymond
Amanda Prorok
49
8
0
29 Sep 2021
Deep Reinforcement Learning Versus Evolution Strategies: A Comparative
  Survey
Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Survey
Amjad Yousef Majid
Serge Saaybi
Tomas van Rietbergen
Vincent François-Lavet
R. V. Prasad
Chris Verhoeven
OffRL
135
60
0
28 Sep 2021
Socially Supervised Representation Learning: the Role of Subjectivity in
  Learning Efficient Representations
Socially Supervised Representation Learning: the Role of Subjectivity in Learning Efficient Representations
Julius Taylor
Eleni Nisioti
Clément Moulin-Frier
52
0
0
20 Sep 2021
POAR: Efficient Policy Optimization via Online Abstract State
  Representation Learning
POAR: Efficient Policy Optimization via Online Abstract State Representation Learning
Zhaorun Chen
Siqi Fan
Yuan Tan
Liang Gong
Binhao Chen
Te Sun
David Filliat
Natalia Díaz Rodríguez
Chengliang Liu
OffRL
51
0
0
17 Sep 2021
Dropout's Dream Land: Generalization from Learned Simulators to Reality
Dropout's Dream Land: Generalization from Learned Simulators to Reality
Zac Wellmer
James T. Kwok
SyDa
69
9
0
17 Sep 2021
Reinforcement Learning for Load-balanced Parallel Particle Tracing
Reinforcement Learning for Load-balanced Parallel Particle Tracing
Jiayi Xu
Hanqi Guo
Han-Wei Shen
Mukund Raj
Skylar W. Wurster
Tom Peterka
32
6
0
13 Sep 2021
Federated Ensemble Model-based Reinforcement Learning in Edge Computing
Federated Ensemble Model-based Reinforcement Learning in Edge Computing
Jin Wang
Jia Hu
Jed Mills
Geyong Min
Ming Xia
FedML
60
24
0
12 Sep 2021
APS: Active Pretraining with Successor Features
APS: Active Pretraining with Successor Features
Hao Liu
Pieter Abbeel
120
123
0
31 Aug 2021
Deep Reinforcement Learning at the Edge of the Statistical Precipice
Deep Reinforcement Learning at the Edge of the Statistical Precipice
Rishabh Agarwal
Max Schwarzer
Pablo Samuel Castro
Aaron Courville
Marc G. Bellemare
OffRL
203
680
0
30 Aug 2021
Fractional Transfer Learning for Deep Model-Based Reinforcement Learning
Fractional Transfer Learning for Deep Model-Based Reinforcement Learning
Remo Sasso
M. Sabatelli
M. Wiering
CLLOffRL
74
7
0
14 Aug 2021
Towards real-world navigation with deep differentiable planners
Towards real-world navigation with deep differentiable planners
Shu Ishida
João F. Henriques
OffRL
46
6
0
08 Aug 2021
Policy Gradients Incorporating the Future
Policy Gradients Incorporating the Future
David Venuto
Elaine Lau
Doina Precup
Ofir Nachum
OffRL
101
9
0
04 Aug 2021
High Performance Across Two Atari Paddle Games Using the Same Perceptual
  Control Architecture Without Training
High Performance Across Two Atari Paddle Games Using the Same Perceptual Control Architecture Without Training
T. Gulrez
W. Mansell
26
0
0
04 Aug 2021
Physics-informed Dyna-Style Model-Based Deep Reinforcement Learning for
  Dynamic Control
Physics-informed Dyna-Style Model-Based Deep Reinforcement Learning for Dynamic Control
Xin-Yang Liu
Jian-Xun Wang
AI4CE
106
42
0
31 Jul 2021
Human-Level Reinforcement Learning through Theory-Based Modeling,
  Exploration, and Planning
Human-Level Reinforcement Learning through Theory-Based Modeling, Exploration, and Planning
Pedro Tsividis
J. Loula
Jake Burga
Nathan Foss
Andres Campero
Thomas Pouncy
S. Gershman
J. Tenenbaum
LM&Ro
59
48
0
27 Jul 2021
Critic Guided Segmentation of Rewarding Objects in First-Person Views
Critic Guided Segmentation of Rewarding Objects in First-Person Views
Andrew Melnik
Augustin Harter
C. Limberg
Krishan Rana
Niko Sünderhauf
Helge J. Ritter
EgoV
60
14
0
20 Jul 2021
Vision-Based Autonomous Car Racing Using Deep Imitative Reinforcement
  Learning
Vision-Based Autonomous Car Racing Using Deep Imitative Reinforcement Learning
Peide Cai
Hengli Wang
Huaiyang Huang
Yuxuan Liu
Ming-Yuan Liu
53
66
0
18 Jul 2021
High-Accuracy Model-Based Reinforcement Learning, a Survey
High-Accuracy Model-Based Reinforcement Learning, a Survey
Aske Plaat
W. Kosters
Mike Preuss
OffRL
75
37
0
17 Jul 2021
Towards an Interpretable Latent Space in Structured Models for Video
  Prediction
Towards an Interpretable Latent Space in Structured Models for Video Prediction
Rushil Gupta
Vishal Sharma
Yash Jain
Yitao Liang
Guy Van den Broeck
Parag Singla
25
1
0
16 Jul 2021
PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided
  Exploration
PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided Exploration
Yuda Song
Wen Sun
114
21
0
15 Jul 2021
The Role of Pretrained Representations for the OOD Generalization of
  Reinforcement Learning Agents
The Role of Pretrained Representations for the OOD Generalization of Reinforcement Learning Agents
Andrea Dittadi
Frederik Trauble
M. Wuthrich
Felix Widmaier
Peter V. Gehler
Ole Winther
Francesco Locatello
Olivier Bachem
Bernhard Schölkopf
Stefan Bauer
OOD
110
16
0
12 Jul 2021
CoBERL: Contrastive BERT for Reinforcement Learning
CoBERL: Contrastive BERT for Reinforcement Learning
Andrea Banino
Adria Puidomenech Badia
Jacob Walker
Tim Scholtes
Jovana Mitrović
Charles Blundell
OffRL
88
36
0
12 Jul 2021
RRL: Resnet as representation for Reinforcement Learning
RRL: Resnet as representation for Reinforcement Learning
Rutav Shah
Vikash Kumar
OffRL
109
115
0
07 Jul 2021
Learning a Generative Transition Model for Uncertainty-Aware Robotic
  Manipulation
Learning a Generative Transition Model for Uncertainty-Aware Robotic Manipulation
Lars Berscheid
Pascal Meissner
Torsten Kröger
36
2
0
06 Jul 2021
Ensemble and Auxiliary Tasks for Data-Efficient Deep Reinforcement
  Learning
Ensemble and Auxiliary Tasks for Data-Efficient Deep Reinforcement Learning
Muhammad Rizki Maulana
W. Lee
55
1
0
05 Jul 2021
Sample Efficient Reinforcement Learning via Model-Ensemble Exploration
  and Exploitation
Sample Efficient Reinforcement Learning via Model-Ensemble Exploration and Exploitation
Yaowen Yao
Li Xiao
Zhicheng An
Wanpeng Zhang
Dijun Luo
101
21
0
05 Jul 2021
Improve Agents without Retraining: Parallel Tree Search with Off-Policy
  Correction
Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction
Assaf Hallak
Gal Dalal
Steven Dalton
I. Frosio
Shie Mannor
Gal Chechik
OffRLOnRL
103
10
0
04 Jul 2021
Supervised Off-Policy Ranking
Supervised Off-Policy Ranking
Yue Jin
Yue Zhang
Tao Qin
Xudong Zhang
Jian Yuan
Houqiang Li
Tie-Yan Liu
OffRL
70
6
0
03 Jul 2021
Classical Planning in Deep Latent Space
Classical Planning in Deep Latent Space
Masataro Asai
Hiroshi Kajino
A. Fukunaga
Christian Muise
VLM
93
19
0
30 Jun 2021
Learning Task Informed Abstractions
Learning Task Informed Abstractions
Xiang Fu
Ge Yang
Pulkit Agrawal
Tommi Jaakkola
116
69
0
29 Jun 2021
Predictive Control Using Learned State Space Models via Rolling Horizon
  Evolution
Predictive Control Using Learned State Space Models via Rolling Horizon Evolution
Alvaro Ovalle
Simon Lucas
40
0
0
25 Jun 2021
FitVid: Overfitting in Pixel-Level Video Prediction
FitVid: Overfitting in Pixel-Level Video Prediction
Mohammad Babaeizadeh
M. Saffar
Suraj Nair
Sergey Levine
Chelsea Finn
D. Erhan
VLM
113
84
0
24 Jun 2021
Uncertainty-Aware Model-Based Reinforcement Learning with Application to
  Autonomous Driving
Uncertainty-Aware Model-Based Reinforcement Learning with Application to Autonomous Driving
Jingda Wu
Zhiyu Huang
Chen Lv
64
7
0
23 Jun 2021
Goal-Directed Planning by Reinforcement Learning and Active Inference
Goal-Directed Planning by Reinforcement Learning and Active Inference
Dongqi Han
Kenji Doya
Jun Tani
53
2
0
18 Jun 2021
Temporal Predictive Coding For Model-Based Planning In Latent Space
Temporal Predictive Coding For Model-Based Planning In Latent Space
Tung D. Nguyen
Rui Shu
Tu Pham
Hung Bui
Stefano Ermon
OffRL
103
59
0
14 Jun 2021
Recomposing the Reinforcement Learning Building Blocks with
  Hypernetworks
Recomposing the Reinforcement Learning Building Blocks with Hypernetworks
Shai Keynan
Elad Sarafian
Sarit Kraus
OffRL
97
30
0
12 Jun 2021
GDI: Rethinking What Makes Reinforcement Learning Different From
  Supervised Learning
GDI: Rethinking What Makes Reinforcement Learning Different From Supervised Learning
Jiajun Fan
Changnan Xiao
Yue Huang
OffRL
91
10
0
11 Jun 2021
Pretrained Encoders are All You Need
Pretrained Encoders are All You Need
Mina Khan
P. Srivatsa
Advait Rane
Shriram Chenniappa
Rishabh Anand
Sherjil Ozair
Pattie Maes
SSLVLM
81
6
0
09 Jun 2021
Pretraining Representations for Data-Efficient Reinforcement Learning
Pretraining Representations for Data-Efficient Reinforcement Learning
Max Schwarzer
Nitarshan Rajkumar
Michael Noukhovitch
Ankesh Anand
Laurent Charlin
Devon Hjelm
Philip Bachman
Aaron Courville
OffRL
113
118
0
09 Jun 2021
Vector Quantized Models for Planning
Vector Quantized Models for Planning
Sherjil Ozair
Yazhe Li
Ali Razavi
Ioannis Antonoglou
Aaron van den Oord
Oriol Vinyals
OffRL
94
51
0
08 Jun 2021
Learning Markov State Abstractions for Deep Reinforcement Learning
Learning Markov State Abstractions for Deep Reinforcement Learning
Cameron Allen
Neev Parikh
Omer Gottesman
George Konidaris
BDLOffRL
117
39
0
08 Jun 2021
PlayVirtual: Augmenting Cycle-Consistent Virtual Trajectories for
  Reinforcement Learning
PlayVirtual: Augmenting Cycle-Consistent Virtual Trajectories for Reinforcement Learning
Tao Yu
Cuiling Lan
Wenjun Zeng
Mingxiao Feng
Zhizheng Zhang
Zhibo Chen
OffRL
101
46
0
08 Jun 2021
Control-Oriented Model-Based Reinforcement Learning with Implicit
  Differentiation
Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation
Evgenii Nikishin
Romina Abachi
Rishabh Agarwal
Pierre-Luc Bacon
OffRL
96
38
0
06 Jun 2021
A Consciousness-Inspired Planning Agent for Model-Based Reinforcement
  Learning
A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning
Mingde Zhao
Zhen Liu
Sitao Luan
Shuyuan Zhang
Doina Precup
Yoshua Bengio
134
37
0
03 Jun 2021
Pathdreamer: A World Model for Indoor Navigation
Pathdreamer: A World Model for Indoor Navigation
Jing Yu Koh
Honglak Lee
Yinfei Yang
Jason Baldridge
Peter Anderson
98
87
0
18 May 2021
Utilizing Skipped Frames in Action Repeats via Pseudo-Actions
Utilizing Skipped Frames in Action Repeats via Pseudo-Actions
Taisei Hashimoto
Yoshimasa Tsuruoka
29
0
0
07 May 2021
DriveGAN: Towards a Controllable High-Quality Neural Simulation
DriveGAN: Towards a Controllable High-Quality Neural Simulation
S. Kim
Jonah Philion
Antonio Torralba
Sanja Fidler
100
119
0
30 Apr 2021
MBRL-Lib: A Modular Library for Model-based Reinforcement Learning
MBRL-Lib: A Modular Library for Model-based Reinforcement Learning
Luis Pineda
Brandon Amos
Amy Zhang
Nathan Lambert
Roberto Calandra
OffRL
84
47
0
20 Apr 2021
Adaptive learning for financial markets mixing model-based and
  model-free RL for volatility targeting
Adaptive learning for financial markets mixing model-based and model-free RL for volatility targeting
Eric Benhamou
David Saltiel
S. Tabachnik
Sui Kai Wong
François Chareyron
OOD
93
4
0
19 Apr 2021
Planning with Expectation Models for Control
Planning with Expectation Models for Control
Katya Kudashkina
Yi Wan
Abhishek Naik
R. Sutton
OffRL
37
0
0
17 Apr 2021
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