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Efficient Model-Based Reinforcement Learning through Optimistic Policy
  Search and Planning

Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning

15 June 2020
Sebastian Curi
Felix Berkenkamp
Andreas Krause
ArXivPDFHTML

Papers citing "Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning"

19 / 19 papers shown
Title
EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning
EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning
Siddharth Aravindan
Dixant Mittal
Wee Sun Lee
BDL
79
0
0
17 Jan 2025
ActSafe: Active Exploration with Safety Constraints for Reinforcement Learning
ActSafe: Active Exploration with Safety Constraints for Reinforcement Learning
Yarden As
Bhavya Sukhija
Lenart Treven
Carmelo Sferrazza
Stelian Coros
Andreas Krause
33
1
0
12 Oct 2024
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling
Jasmine Bayrooti
Carl Henrik Ek
Amanda Prorok
42
0
0
07 Oct 2024
NeoRL: Efficient Exploration for Nonepisodic RL
NeoRL: Efficient Exploration for Nonepisodic RL
Bhavya Sukhija
Lenart Treven
Florian Dorfler
Stelian Coros
Andreas Krause
OffRL
33
0
0
03 Jun 2024
Ensemble sampling for linear bandits: small ensembles suffice
Ensemble sampling for linear bandits: small ensembles suffice
David Janz
A. Litvak
Csaba Szepesvári
30
1
0
14 Nov 2023
Distributionally Robust Model-based Reinforcement Learning with Large
  State Spaces
Distributionally Robust Model-based Reinforcement Learning with Large State Spaces
Shyam Sundhar Ramesh
Pier Giuseppe Sessa
Yifan Hu
Andreas Krause
Ilija Bogunovic
OOD
42
10
0
05 Sep 2023
Model-Based Uncertainty in Value Functions
Model-Based Uncertainty in Value Functions
Carlos E. Luis
A. Bottero
Julia Vinogradska
Felix Berkenkamp
Jan Peters
36
13
0
24 Feb 2023
Exploration via Planning for Information about the Optimal Trajectory
Exploration via Planning for Information about the Optimal Trajectory
Viraj Mehta
I. Char
J. Abbate
R. Conlin
M. Boyer
Stefano Ermon
J. Schneider
W. Neiswanger
OffRL
27
6
0
06 Oct 2022
Safe Reinforcement Learning via Confidence-Based Filters
Safe Reinforcement Learning via Confidence-Based Filters
Sebastian Curi
Armin Lederer
Sandra Hirche
Andreas Krause
OffRL
24
4
0
04 Jul 2022
Gradient-Based Trajectory Optimization With Learned Dynamics
Gradient-Based Trajectory Optimization With Learned Dynamics
Bhavya Sukhija
Nathanael Kohler
Miguel Zamora
Simon Zimmermann
Sebastian Curi
Andreas Krause
Stelian Coros
30
9
0
09 Apr 2022
User-Oriented Robust Reinforcement Learning
User-Oriented Robust Reinforcement Learning
Haoyi You
Beichen Yu
Haiming Jin
Zhaoxing Yang
Jiahui Sun
OffRL
32
0
0
15 Feb 2022
Representation Learning for Online and Offline RL in Low-rank MDPs
Representation Learning for Online and Offline RL in Low-rank MDPs
Masatoshi Uehara
Xuezhou Zhang
Wen Sun
OffRL
62
126
0
09 Oct 2021
Exploration in Deep Reinforcement Learning: From Single-Agent to
  Multiagent Domain
Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain
Jianye Hao
Tianpei Yang
Hongyao Tang
Chenjia Bai
Jinyi Liu
Zhaopeng Meng
Peng Liu
Zhen Wang
OffRL
36
92
0
14 Sep 2021
Efficient Model-Based Multi-Agent Mean-Field Reinforcement Learning
Efficient Model-Based Multi-Agent Mean-Field Reinforcement Learning
Barna Pásztor
Ilija Bogunovic
Andreas Krause
28
41
0
08 Jul 2021
Koopman Spectrum Nonlinear Regulators and Efficient Online Learning
Koopman Spectrum Nonlinear Regulators and Efficient Online Learning
Motoya Ohnishi
Isao Ishikawa
Kendall Lowrey
Masahiro Ikeda
Sham Kakade
Yoshinobu Kawahara
21
5
0
30 Jun 2021
Safe Chance Constrained Reinforcement Learning for Batch Process Control
Safe Chance Constrained Reinforcement Learning for Batch Process Control
M. Mowbray
Panagiotis Petsagkourakis
Ehecatl Antonio del Rio Chanona
Dongda Zhang
OffRL
34
34
0
23 Apr 2021
Combining Pessimism with Optimism for Robust and Efficient Model-Based
  Deep Reinforcement Learning
Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning
Sebastian Curi
Ilija Bogunovic
Andreas Krause
39
17
0
18 Mar 2021
Information Theoretic Regret Bounds for Online Nonlinear Control
Information Theoretic Regret Bounds for Online Nonlinear Control
Sham Kakade
A. Krishnamurthy
Kendall Lowrey
Motoya Ohnishi
Wen Sun
31
117
0
22 Jun 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,675
0
05 Dec 2016
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