Prioritized Sweeping
Prioritized Sweeping is a model-based reinforcement learning algorithm that belongs to the class of dynamic programming methods, distinguished by its use of a priority queue to selectively update state values based on the magnitude of their backed-up errors, thereby accelerating convergence in sparse environments.
17
Publications
1.6K
Citations
42
Authors
21
Institutions
Publications per year
2017–2026
2
Parents
17
1–5 of 17
42
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University of Alberta
Edmonton, Canada
4 h-index
13 publications
654 citations
Massachusetts Institute of Technology
Cambridge, United States
3 h-index
6 publications
2.2K citations
University of Liège
Liège, Belgium
2 h-index
4 publications
60 citations
The University of Texas at Austin
Austin, United States
1 h-index
2 publications
44 citations
Kaohsiung Medical University
Kaohsiung City, Taiwan
1 h-index
1 publications
19 citations

Beijing Institute of Technology
Beijing, China
1 h-index
5 publications
310 citations
Rutgers, The State University of New Jersey
New Brunswick, United States
1 h-index
2 publications
26 citations
National Chung Cheng University
Minxiong, Taiwan
1 h-index
1 publications
19 citations
1–8 of 21
Repository · 2 publications · 132 citations
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2 publications · 1.1K citations
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1 publications · 30 citations
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1 publications · 62 citations
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1 publications · 70 citations
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