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The initial phrase of the article and the link to constraint satisfaction give sufficient context |
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In [[artificial intelligence]] and [[operations research]], '''hierarchical constraint satisfaction (HCS)''' is a method of handling [[constraint satisfaction]] problems where the [[Variable (mathematics)|variables]] have large domains by exploiting their internal structure.<ref name="wiley">{{Cite journal|last=Mackworth|first=Alan K.|last2=Mulder|first2=Jan A.|last3=Havens|first3=William S.|date=1985-01-01|title=Hierarchical arc consistency: exploiting structured domains in constraint satisfaction problems|journal=Computational Intelligence|language=en|volume=1|issue=1|pages=118–126|doi=10.1111/j.1467-8640.1985.tb00064.x|issn=1467-8640}}</ref>▼
For many real-world problems the ___domain elements cluster together into sets with common properties and relations. This structure can be represented as a hierarchy and is [[Partially ordered set|partially ordered]] on the subset of a relation. The expectation is that the domains are structured so that the elements of a set frequently share consistency properties permitting them to be retained or eliminated as a unit. Thus, if some elements of a set satisfy a [[constraint (mathematics)|constraint]], but not all, the subsets of the set are considered. In this way, if no elements of a set can satisfy the constraint the whole set can be discarded. Thus, structuring the ___domain helps in considering sets of elements all at a time and hence helps in pruning the search space more quickly.<ref name="sciencedirect">{{Cite journal|date=1993-07-01|title=Hierarchical constraint logic programming|journal=The Journal of Logic Programming|language=en|volume=16|issue=3–4|pages=277–318|doi=10.1016/0743-1066(93)90046-J|issn=0743-1066|last1=Wilson|first1=Molly|last2=Borning|first2=Alan|doi-access=free}}</ref>▼
▲In [[artificial intelligence]] and [[operations research]], '''hierarchical constraint satisfaction (HCS)''' is a method of handling [[constraint satisfaction]] problems where the [[Variable (mathematics)|variables]] have large domains by exploiting their internal structure.
==References==
{{Reflist}}
▲For many real-world problems the ___domain elements cluster together into sets with common properties and relations. This structure can be represented as a hierarchy and is [[Partially ordered set|partially ordered]] on the subset of a relation. The expectation is that the domains are structured so that the elements of a set frequently share consistency properties permitting them to be retained or eliminated as a unit. Thus, if some elements of a set satisfy a [[constraint (mathematics)|constraint]], but not all, the subsets of the set are considered. In this way, if no elements of a set can satisfy the constraint the whole set can be discarded. Thus, structuring the ___domain helps in considering sets of elements all at a time and hence helps in pruning the search space more quickly.
▲[[Category:Constraint satisfaction]]
{{Mathapplied-stub}}
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