Distributed Constraint Optimization is a computational framework within multi-agent systems that coordinates autonomous agents to collectively optimize a global objective function subject to local constraints, distinguished by its decomposition of decision-making across distributed agents without centralized control.
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392
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178
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2017–2026
68
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Publications
235
Adopt: asynchronous distributed constraint optimization with quality guarantees
Pragnesh Jay Modi, Wei‐Min Shen, Milind Tambe et al. · Artificial Intelligence · 2004 · 762 citations
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392
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1–5 of 392
Institutions
178
University of Southern California
Los Angeles, United States
20 h-index
66 publications
6.8K citations
École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland
16 h-index
34 publications
2.3K citations
Ben-Gurion University of the Negev
Beersheba, Israel
15 h-index
43 publications
2.1K citations
Kyushu University
Fukuoka, Japan
12 h-index
17 publications
701 citations
University of Massachusetts Amherst
Amherst Center, United States
11 h-index
15 publications
1.4K citations
Carnegie Mellon University
Pittsburgh, United States
11 h-index
21 publications
867 citations
New Mexico State University
Las Cruces, United States
11 h-index
28 publications
735 citations
University of Southampton
Southampton, United Kingdom
8 h-index
15 publications
481 citations
1–8 of 178
Venues
- IEEE Transactions on Automatic Control
10 publications · 1.5K citations
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- Adaptive Agents and Multi-Agents Systems
Conference · 10 publications · 328 citations
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- Journal of Artificial Intelligence Research
JAIR · 8 publications · 567 citations
8
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- Proceedings of the AAAI Conference on Artificial Intelligence
Conference · 8 publications · 334 citations
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- IEEE Transactions on Cybernetics
7 publications · 448 citations
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