Task Assignment Learning
Task Assignment Learning is a multi-robot learning framework that specifically addresses the acquisition of optimal task-to-robot allocation policies through experience-driven adaptation, distinguishing itself from general coordination mechanisms by its focus on learning assignment strategies that maximize collective performance in dynamic and uncertain environments.
39
Publications
1.6K
Citations
163
Authors
71
Institutions
Publications per year
2017–2026
28
Parents
39
1–5 of 39
163
University of Electronic Science and Technology of China, China
2 publications · 56 citations
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1–5 of 163
71

City University of Hong Kong
Hong Kong, Hong Kong
3 h-index
6 publications
328 citations
Aalborg University
Aalborg, Denmark
2 h-index
8 publications
228 citations

Soochow University
Suzhou, China
2 h-index
2 publications
41 citations
Jilin University
Changchun, China
2 h-index
8 publications
148 citations

University of Hong Kong
Pok Fu Lam, Hong Kong
2 h-index
2 publications
74 citations

University of Electronic Science and Technology of China
Chengdu, China
2 h-index
6 publications
168 citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
2 h-index
5 publications
161 citations
Tianjin University
Tianjin, China
1 h-index
4 publications
520 citations
1–8 of 71
Repository · 3 publications · 48 citations
3
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2 publications · 130 citations
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2 publications · 102 citations
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2 publications · 101 citations
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FGCS · 1 publications · 106 citations
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