Graph-based Multi-agent Learning
Graph-Based Multi-Agent Learning is a multi-agent learning framework in which the interactions, dependencies, or communication structures among agents are explicitly modeled as a graph, enabling the use of graph-based representations and algorithms to facilitate coordinated decision-making and learning.
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4K
Citations
318
Authors
128
Institutions
Publications per year
2017–2026
74
Parents
86
Pai Zheng, Liqiao Xia, Chengxi Li et al. · Journal of Manufacturing Systems · 2021 · 203 citations · Full text
Engineering, Industrial Engineering, Manufacturing Engineering +12
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128

Chinese Academy of Sciences
Beijing, China
6 h-index
14 publications
679 citations
Nanyang Technological University
Singapore, Singapore
5 h-index
10 publications
679 citations
University of California, Los Angeles
Los Angeles, United States
5 h-index
12 publications
560 citations

Southeast University
Nanjing, China
4 h-index
11 publications
451 citations
Rutgers, The State University of New Jersey
New Brunswick, United States
4 h-index
5 publications
278 citations
Tianjin University
Tianjin, China
4 h-index
8 publications
656 citations
École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland
4 h-index
9 publications
227 citations

University of Electronic Science and Technology of China
Chengdu, China
4 h-index
14 publications
618 citations
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Repository · 8 publications · 183 citations
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7 publications · 242 citations
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3 publications · 219 citations
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3 publications · 112 citations
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2 publications · 88 citations
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1–5