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Continuous Doubly Constrained Batch Reinforcement Learning
v1v2v3v4 (latest)

Continuous Doubly Constrained Batch Reinforcement Learning

18 February 2021
Rasool Fakoor
Jonas W. Mueller
Kavosh Asadi
Pratik Chaudhari
Alex Smola
    OffRL
ArXiv (abs)PDFHTML

Papers citing "Continuous Doubly Constrained Batch Reinforcement Learning"

39 / 39 papers shown
Title
Benchmarks for Deep Off-Policy Evaluation
Benchmarks for Deep Off-Policy Evaluation
Justin Fu
Mohammad Norouzi
Ofir Nachum
George Tucker
Ziyun Wang
...
Yutian Chen
Aviral Kumar
Cosmin Paduraru
Sergey Levine
T. Paine
ELMOffRL
78
103
0
30 Mar 2021
Regularized Behavior Value Estimation
Regularized Behavior Value Estimation
Çağlar Gülçehre
Sergio Gomez Colmenarejo
Ziyun Wang
Jakub Sygnowski
T. Paine
Konrad Zolna
Yutian Chen
Matthew W. Hoffman
Razvan Pascanu
Nando de Freitas
OffRL
68
38
0
17 Mar 2021
Is Pessimism Provably Efficient for Offline RL?
Is Pessimism Provably Efficient for Offline RL?
Ying Jin
Zhuoran Yang
Zhaoran Wang
OffRL
172
358
0
30 Dec 2020
The Importance of Pessimism in Fixed-Dataset Policy Optimization
The Importance of Pessimism in Fixed-Dataset Policy Optimization
Jacob Buckman
Carles Gelada
Marc G. Bellemare
OffRL
84
138
0
15 Sep 2020
EMaQ: Expected-Max Q-Learning Operator for Simple Yet Effective Offline
  and Online RL
EMaQ: Expected-Max Q-Learning Operator for Simple Yet Effective Offline and Online RL
Seyed Kamyar Seyed Ghasemipour
Dale Schuurmans
S. Gu
OffRL
280
121
0
21 Jul 2020
Hyperparameter Selection for Offline Reinforcement Learning
Hyperparameter Selection for Offline Reinforcement Learning
T. Paine
Cosmin Paduraru
Andrea Michi
Çağlar Gülçehre
Konrad Zolna
Alexander Novikov
Ziyun Wang
Nando de Freitas
GPOffRL
176
148
0
17 Jul 2020
DDPG++: Striving for Simplicity in Continuous-control Off-Policy
  Reinforcement Learning
DDPG++: Striving for Simplicity in Continuous-control Off-Policy Reinforcement Learning
Rasool Fakoor
Pratik Chaudhari
Alex Smola
OffRL
35
4
0
26 Jun 2020
Critic Regularized Regression
Critic Regularized Regression
Ziyun Wang
Alexander Novikov
Konrad Zolna
Jost Tobias Springenberg
Scott E. Reed
...
Noah Y. Siegel
J. Merel
Çağlar Gülçehre
N. Heess
Nando de Freitas
OffRL
150
327
0
26 Jun 2020
Conservative Q-Learning for Offline Reinforcement Learning
Conservative Q-Learning for Offline Reinforcement Learning
Aviral Kumar
Aurick Zhou
George Tucker
Sergey Levine
OffRLOnRL
140
1,815
0
08 Jun 2020
MOPO: Model-based Offline Policy Optimization
MOPO: Model-based Offline Policy Optimization
Tianhe Yu
G. Thomas
Lantao Yu
Stefano Ermon
James Zou
Sergey Levine
Chelsea Finn
Tengyu Ma
OffRL
76
770
0
27 May 2020
MOReL : Model-Based Offline Reinforcement Learning
MOReL : Model-Based Offline Reinforcement Learning
Rahul Kidambi
Aravind Rajeswaran
Praneeth Netrapalli
Thorsten Joachims
OffRL
96
672
0
12 May 2020
Controlling Overestimation Bias with Truncated Mixture of Continuous
  Distributional Quantile Critics
Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics
Arsenii Kuznetsov
Pavel Shvechikov
Alexander Grishin
Dmitry Vetrov
230
193
0
08 May 2020
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on
  Open Problems
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
Sergey Levine
Aviral Kumar
George Tucker
Justin Fu
OffRLGP
558
2,029
0
04 May 2020
D4RL: Datasets for Deep Data-Driven Reinforcement Learning
D4RL: Datasets for Deep Data-Driven Reinforcement Learning
Justin Fu
Aviral Kumar
Ofir Nachum
George Tucker
Sergey Levine
GPOffRL
223
1,368
0
15 Apr 2020
Keep Doing What Worked: Behavioral Modelling Priors for Offline
  Reinforcement Learning
Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning
Noah Y. Siegel
Jost Tobias Springenberg
Felix Berkenkamp
A. Abdolmaleki
Michael Neunert
Thomas Lampe
Roland Hafner
Nicolas Heess
Martin Riedmiller
OffRL
58
283
0
19 Feb 2020
Maxmin Q-learning: Controlling the Estimation Bias of Q-learning
Maxmin Q-learning: Controlling the Estimation Bias of Q-learning
Qingfeng Lan
Yangchen Pan
Alona Fyshe
Martha White
63
179
0
16 Feb 2020
Interpretable Off-Policy Evaluation in Reinforcement Learning by
  Highlighting Influential Transitions
Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions
Omer Gottesman
Joseph D. Futoma
Yao Liu
Soanli Parbhoo
Leo Anthony Celi
Emma Brunskill
Finale Doshi-Velez
OffRL
208
57
0
10 Feb 2020
The problem with DDPG: understanding failures in deterministic
  environments with sparse rewards
The problem with DDPG: understanding failures in deterministic environments with sparse rewards
Guillaume Matheron
Nicolas Perrin
Olivier Sigaud
37
67
0
26 Nov 2019
Behavior Regularized Offline Reinforcement Learning
Behavior Regularized Offline Reinforcement Learning
Yifan Wu
George Tucker
Ofir Nachum
OffRL
89
687
0
26 Nov 2019
Advantage-Weighted Regression: Simple and Scalable Off-Policy
  Reinforcement Learning
Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning
Xue Bin Peng
Aviral Kumar
Grace Zhang
Sergey Levine
OffRL
145
561
0
01 Oct 2019
Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction
Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction
Aviral Kumar
Justin Fu
George Tucker
Sergey Levine
OffRLOnRL
132
1,060
0
03 Jun 2019
P3O: Policy-on Policy-off Policy Optimization
P3O: Policy-on Policy-off Policy Optimization
Rasool Fakoor
Pratik Chaudhari
Alex Smola
OffRL
66
54
0
05 May 2019
Challenges of Real-World Reinforcement Learning
Challenges of Real-World Reinforcement Learning
Gabriel Dulac-Arnold
D. Mankowitz
Todd Hester
OffRL
79
548
0
29 Apr 2019
Batch Policy Learning under Constraints
Batch Policy Learning under Constraints
Hoang Minh Le
Cameron Voloshin
Yisong Yue
OffRL
58
331
0
20 Mar 2019
Off-Policy Deep Reinforcement Learning without Exploration
Off-Policy Deep Reinforcement Learning without Exploration
Scott Fujimoto
David Meger
Doina Precup
OffRLBDL
228
1,613
0
07 Dec 2018
An Algorithmic Perspective on Imitation Learning
An Algorithmic Perspective on Imitation Learning
Takayuki Osa
Joni Pajarinen
Gerhard Neumann
J. Andrew Bagnell
Pieter Abbeel
Jan Peters
88
845
0
16 Nov 2018
Addressing Function Approximation Error in Actor-Critic Methods
Addressing Function Approximation Error in Actor-Critic Methods
Scott Fujimoto
H. V. Hoof
David Meger
OffRL
175
5,187
0
26 Feb 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
311
8,352
0
04 Jan 2018
Proximal Policy Optimization Algorithms
Proximal Policy Optimization Algorithms
John Schulman
Filip Wolski
Prafulla Dhariwal
Alec Radford
Oleg Klimov
OffRL
499
19,065
0
20 Jul 2017
Deep Q-learning from Demonstrations
Deep Q-learning from Demonstrations
Todd Hester
Matej Vecerík
Olivier Pietquin
Marc Lanctot
Tom Schaul
...
Gabriel Dulac-Arnold
Ian Osband
J. Agapiou
Joel Z Leibo
A. Gruslys
OffRL
54
155
0
12 Apr 2017
Count-Based Exploration with Neural Density Models
Count-Based Exploration with Neural Density Models
Georg Ostrovski
Marc G. Bellemare
Aaron van den Oord
Rémi Munos
84
623
0
03 Mar 2017
Deep Reinforcement Learning: An Overview
Deep Reinforcement Learning: An Overview
Yuxi Li
OffRLVLM
175
1,539
0
25 Jan 2017
Unifying Count-Based Exploration and Intrinsic Motivation
Unifying Count-Based Exploration and Intrinsic Motivation
Marc G. Bellemare
S. Srinivasan
Georg Ostrovski
Tom Schaul
D. Saxton
Rémi Munos
174
1,478
0
06 Jun 2016
Dueling Network Architectures for Deep Reinforcement Learning
Dueling Network Architectures for Deep Reinforcement Learning
Ziyun Wang
Tom Schaul
Matteo Hessel
H. V. Hasselt
Marc Lanctot
Nando de Freitas
OffRL
91
3,755
0
20 Nov 2015
Deep Reinforcement Learning with Double Q-learning
Deep Reinforcement Learning with Double Q-learning
H. V. Hasselt
A. Guez
David Silver
OffRL
170
7,641
0
22 Sep 2015
Continuous control with deep reinforcement learning
Continuous control with deep reinforcement learning
Timothy Lillicrap
Jonathan J. Hunt
Alexander Pritzel
N. Heess
Tom Erez
Yuval Tassa
David Silver
Daan Wierstra
320
13,248
0
09 Sep 2015
Trust Region Policy Optimization
Trust Region Policy Optimization
John Schulman
Sergey Levine
Philipp Moritz
Michael I. Jordan
Pieter Abbeel
277
6,776
0
19 Feb 2015
A Reduction of Imitation Learning and Structured Prediction to No-Regret
  Online Learning
A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning
Stéphane Ross
Geoffrey J. Gordon
J. Andrew Bagnell
OffRL
222
3,221
0
02 Nov 2010
Estimating divergence functionals and the likelihood ratio by convex
  risk minimization
Estimating divergence functionals and the likelihood ratio by convex risk minimization
X. Nguyen
Martin J. Wainwright
Michael I. Jordan
223
803
0
04 Sep 2008
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