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2005.07404
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Think Too Fast Nor Too Slow: The Computational Trade-off Between Planning And Reinforcement Learning
15 May 2020
Thomas M. Moerland
Anna Deichler
S. Baldi
Joost Broekens
Catholijn M. Jonker
OffRL
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Papers citing
"Think Too Fast Nor Too Slow: The Computational Trade-off Between Planning And Reinforcement Learning"
7 / 7 papers shown
Counting Hours, Counting Losses: The Toll of Unpredictable Work Schedules on Financial Security
Pegah Nokhiz
Aravinda Kanchana Ruwanpathirana
Aditya Bhaskara
Suresh Venkatasubramanian
303
5
0
10 Apr 2025
Multi-Bellman operator for convergence of
Q
Q
Q
-learning with linear function approximation
Diogo S. Carvalho
D. L. McPherson
Francisco S. Melo
256
4
0
28 Sep 2023
Planning and Learning with Adaptive Lookahead
AAAI Conference on Artificial Intelligence (AAAI), 2022
Aviv A. Rosenberg
Assaf Hallak
Shie Mannor
Gal Chechik
Gal Dalal
287
12
0
28 Jan 2022
Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction
Assaf Hallak
Gal Dalal
Steven Dalton
I. Frosio
Shie Mannor
Gal Chechik
OffRL
OnRL
300
11
0
04 Jul 2021
CAMPs: Learning Context-Specific Abstractions for Efficient Planning in Factored MDPs
Conference on Robot Learning (CoRL), 2020
Rohan Chitnis
Tom Silver
Beomjoon Kim
L. Kaelbling
Tomas Lozano-Perez
320
33
0
26 Jul 2020
Model-based Reinforcement Learning: A Survey
Thomas M. Moerland
Joost Broekens
Aske Plaat
Catholijn M. Jonker
OffRL
602
54
0
30 Jun 2020
A Unifying Framework for Reinforcement Learning and Planning
Thomas M. Moerland
Joost Broekens
Aske Plaat
Catholijn M. Jonker
OffRL
583
16
0
26 Jun 2020
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