Centralized Training
Centralized Training is a multi-robot learning framework in which a single, unified model or policy is trained using globally accessible information from all robots, distinguishing it from decentralized approaches by relying on a centralized data aggregation and update process.
170
Publications
8.5K
Citations
620
Authors
216
Institutions
Publications per year
2017–2026
164
Parents
170
1–5 of 170
620
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1–5 of 620
216

Beijing University of Posts and Telecommunications
Beijing, China
11 h-index
27 publications
1K citations
University of Science and Technology of China
Hefei, China
8 h-index
14 publications
493 citations
Tsinghua University
Beijing, China
7 h-index
21 publications
743 citations

Chinese Academy of Sciences
Beijing, China
6 h-index
16 publications
401 citations

University of Electronic Science and Technology of China
Chengdu, China
6 h-index
24 publications
3.6K citations

Zhejiang University
Hangzhou, China
5 h-index
13 publications
1.3K citations
Nanyang Technological University
Singapore, Singapore
5 h-index
8 publications
1.2K citations

Southeast University
Nanjing, China
5 h-index
12 publications
1K citations
1–8 of 216
Repository · 19 publications · 997 citations
16
h-index
9 publications · 654 citations
10
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Conference · 4 publications · 171 citations
5
h-index
2 publications · 76 citations
4
h-index
TMCCI · 2 publications · 83 citations
4
h-index
1–5