Acquiring constraint networks using a SAT-based version space algorithm

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Abstract

Constraint programming is a commonly used technology for solving complex combinatorial problems. However, users of this technology need significant expertise in order to model their problems appropriately. We propose a basis for addressing this problem: a new SAT-based version space algorithm for acquiring constraint networks from examples of solutions and non-solutions of a target problem. An important advantage of the algorithm is the ease with which domain-specific knowledge can be exploited.

Original languageEnglish
Title of host publicationProceedings of the 21st National Conference on Artificial Intelligence and the 18th Innovative Applications of Artificial Intelligence Conference, AAAI-06/IAAI-06
Pages1565-1568
Number of pages4
Publication statusPublished - 2006
Event21st National Conference on Artificial Intelligence and the 18th Innovative Applications of Artificial Intelligence Conference, AAAI-06/IAAI-06 - Boston, MA, United States
Duration: 16 Jul 200620 Jul 2006

Publication series

NameProceedings of the National Conference on Artificial Intelligence
Volume2

Conference

Conference21st National Conference on Artificial Intelligence and the 18th Innovative Applications of Artificial Intelligence Conference, AAAI-06/IAAI-06
Country/TerritoryUnited States
CityBoston, MA
Period16/07/0620/07/06

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