Abstract
Reinforcing local consistency, in particular arc consistency, has attracted the attention of many researchers due to its preeminent role in efficient CSP (constraint satisfaction problem) solving. Many centralized arc consistency techniques have been proposed for binary constraints. But, only very few reports are available addressing directly to general constraints for centralized framework and not for distributed one. The main contribution of this work consists in proposing a new generalized schema (called GDRAC) for reinforcing arc-consistency on general constraint networks (CNs) in an asynchronous and distributed manner. The experimental comparative evaluations show the high performance of our approach to general constraints.
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Hassine, A.B., Ghedira, K., Ho, T.B. (2004). New Distributed Filtering-Consistency Approach to General Networks. In: Orchard, B., Yang, C., Ali, M. (eds) Innovations in Applied Artificial Intelligence. IEA/AIE 2004. Lecture Notes in Computer Science(), vol 3029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24677-0_73
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DOI: https://doi.org/10.1007/978-3-540-24677-0_73
Publisher Name: Springer, Berlin, Heidelberg
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