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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Bibliographic Details
Published in:Annals of mathematics and artificial intelligence Vol. 83; no. 1; pp. 99 - 119
Main Authors: Berend, Daniel, Meisels, Amnon, Peri, Or
Format: Journal Article
Language:English
Published: Cham Springer International Publishing 01.05.2018
Springer
Springer Nature B.V
Subjects:
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
Online Access:Get full text
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Summary: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.
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ISSN:1012-2443
1573-7470
DOI:10.1007/s10472-018-9582-1