Probabilistic optimal solution assessment for DCOPs

Distributed Constraint Optimization Problems (DCOPs) are widely used in Multi-Agent Systems for coordination and scheduling. The present paper proposes a heuristic algorithm that uses probabilistic assessment of the optimal solution in order to quickly find a solution that is not far from the optima...

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Vydané v:Annals of mathematics and artificial intelligence Ročník 83; číslo 1; s. 99 - 119
Hlavní autori: Berend, Daniel, Meisels, Amnon, Peri, Or
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Cham Springer International Publishing 01.05.2018
Springer
Springer Nature B.V
Predmet:
Algorithms
Artificial Intelligence
Complex Systems
Computer Science
Expected values
Heuristic
Heuristic methods
Mathematics
Multiagent systems
Optimization
Performance evaluation
Search algorithms
Variables
62P04
90-04
Constraints optimization
68T04
DCOP
ISSN:1012-2443, 1573-7470
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Shrnutí:Distributed Constraint Optimization Problems (DCOPs) are widely used in Multi-Agent Systems for coordination and scheduling. The present paper proposes a heuristic algorithm that uses probabilistic assessment of the optimal solution in order to quickly find a solution that is not far from the optimal one. The heuristic assessment uses two passes by the agents to produce a high-quality solution. Extensive performance evaluation demonstrates that the solution of the proposed probabilistic assessment algorithm is indeed very close to the optimum, on smaller problems where this could be measured. In larger set-ups, the quality of the solution is demonstrated relatively to standard incomplete search algorithms.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1012-2443
1573-7470
DOI:10.1007/s10472-018-9582-1