TítuloBnB-ADOPT+ with Several Soft AC Levels
Publication TypeConference Paper
Year of Publication2010
AuthorsGutierrez P, Meseguer P
Conference NameEuropean Conference on Artificial Intelligence (ECAI-10)
Conference LocationLisbon, Portugal
Paginación67-72
Date Published16/08/2010
Palabras clavearc consistency, Distributed constraint optimization, soft constraints
Resumen

Distributed constraint optimization problems can be solved by BnB-ADOPT$^+$, a distributed asynchronous search algorithm. In the centralized case, local consistency techniques applied to constraint optimization have been shown very beneficial to increase performance. In this paper, we combine BnB-ADOPT$^+$ with different levels of soft arc consistency, propagating unconditional deletions caused by either the enforced local consistency or by distributed search. The new algorithm maintains BnB-ADOPT$^+$ optimality and termination. In practice, this approach decreases substantially BnB-ADOPT$^+$ requirements in communication cost and computation effort when solving commonly used benchmarks.