Scalable Multi-agent Learning
Scalable Multi-Agent Learning is a formal framework in multi-agent robot learning that enables the coordination and learning of a large number of agents by maintaining computational efficiency and performance consistency as the system size increases.
105
Publications
6.6K
Citations
405
Authors
117
Institutions
Publications per year
2017–2026
89
Parents
105
1–5 of 105
405
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117
Tsinghua University
Beijing, China
4 h-index
9 publications
227 citations
Carnegie Mellon University
Pittsburgh, United States
4 h-index
7 publications
246 citations
University College London
London, United Kingdom
4 h-index
4 publications
852 citations

Shanghai Jiao Tong University
Shanghai, China
3 h-index
10 publications
844 citations
Nanjing University
Nanjing, China
3 h-index
5 publications
283 citations

Peking University
Beijing, China
3 h-index
6 publications
472 citations

University of Central Florida
Orlando, United States
3 h-index
9 publications
301 citations

University of Edinburgh
Edinburgh, United Kingdom
3 h-index
19 publications
378 citations
1–8 of 117
Repository · 34 publications · 2.9K citations
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Conference · 10 publications · 509 citations
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3 publications · 104 citations
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2 publications · 58 citations
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Conference · 2 publications · 76 citations
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