Abstract
A reason to distribute constraint satisfaction is privacy: agents may not want to share their values, and they may wish to keep constraints as private as possible. In this paper, we present the Distributed Forward Checking algorithm, a natural successor of Asynchronous Backtracking, where some privacy is achieved on agent values. Regarding constraints, we introduce the Partially Known Constraints model, which allow a constraint between two agents to be not completely known by any of them. With these elements, we obtain new solving algorithms that enforce privacy and maintain completeness. Empirical results are provided. © Springer-Verlag 2003.
Cite
CITATION STYLE
Brito, I., & Meseguer, P. (2003). Distributed forward checking. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2833, 801–806. https://doi.org/10.1007/978-3-540-45193-8_56
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