Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/77881
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dc.titleMaintaining generalized arc consistency on Ad-hoc n-ary boolean constraints
dc.contributor.authorCheng, K.C.K.
dc.contributor.authorYap, R.H.C.
dc.date.accessioned2014-07-04T03:09:53Z
dc.date.available2014-07-04T03:09:53Z
dc.date.issued2006
dc.identifier.citationCheng, K.C.K.,Yap, R.H.C. (2006). Maintaining generalized arc consistency on Ad-hoc n-ary boolean constraints. Frontiers in Artificial Intelligence and Applications 141 : 78-82. ScholarBank@NUS Repository.
dc.identifier.isbn9781586036423
dc.identifier.issn09226389
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/77881
dc.description.abstractBinary decision diagrams (BDDs) can compactly rep- resent ad-hoc n-ary Boolean constraints. However, there is no gen- eralized arc consistency (GAC) algorithm which exploit BDDs. For example, the global case constraint by SICStus Prolog for ad-hoc constraints is designed for non-Boolean domains. In this paper, we introduce a new GAC algorithm, bddc, for BDD constraints. Our empirical results demonstrate the advantages of a new BDD-based global constraint-bddc is more efficient both in terms of mem- ory and time than the case constraint when dealing with ad-hoc Boolean constraints. This becomes important as the size of the ad- hoc constraints becomes large. © 2006 The authors.
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.sourcetitleFrontiers in Artificial Intelligence and Applications
dc.description.volume141
dc.description.page78-82
dc.identifier.isiutNOT_IN_WOS
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