About: Hybrid algorithm (constraint satisfaction)

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Within artificial intelligence and operations research for constraint satisfaction a hybrid algorithm solves a constraint satisfaction problem by the combination of two different methods, for example (backtracking, backjumping, etc.) and constraint inference (arc consistency, variable elimination, etc.) Hybrid algorithms exploit the good properties of different methods by applying them to problems they can efficiently solve. For example, search is efficient when the problem has many solutions, while inference is efficient in proving unsatisfiability of overconstrained problems.

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rdfs:label	Hybrid algorithm (constraint satisfaction) (en)
rdfs:comment	Within artificial intelligence and operations research for constraint satisfaction a hybrid algorithm solves a constraint satisfaction problem by the combination of two different methods, for example (backtracking, backjumping, etc.) and constraint inference (arc consistency, variable elimination, etc.) Hybrid algorithms exploit the good properties of different methods by applying them to problems they can efficiently solve. For example, search is efficient when the problem has many solutions, while inference is efficient in proving unsatisfiability of overconstrained problems. (en)
sameAs	Hybrid algorithm (constraint satisfaction)
dbp:wikiPageUsesTemplate	dbt:Cite_book dbt:Multiple_issues dbt:No_footnotes dbt:Refimprove dbt:Context dbt:Clarification_needed
Subject	Constraint programming
prov:wasDerivedFrom	http://en.wikipedia.org/wiki/Hybrid_algorithm_(constraint_satisfaction)?oldid=914699780&ns=0
Wikipage page ID	4194205 (xsd:integer)
page length (characters) of wiki page	6906 (xsd:nonNegativeInteger)
Wikipage revision ID	914699780 (xsd:integer)
Link from a Wikipage to another Wikipage	Local consistency Local search (constraint satisfaction) Backjumping Backtracking Constraint programming Consistency Constraint inference Constraint satisfaction Constraint satisfaction dual problem Constraint satisfaction problem Feedback vertex set Tree (graph theory) Variable elimination dbr:Variable_conditioning
has abstract	Within artificial intelligence and operations research for constraint satisfaction a hybrid algorithm solves a constraint satisfaction problem by the combination of two different methods, for example (backtracking, backjumping, etc.) and constraint inference (arc consistency, variable elimination, etc.) Hybrid algorithms exploit the good properties of different methods by applying them to problems they can efficiently solve. For example, search is efficient when the problem has many solutions, while inference is efficient in proving unsatisfiability of overconstrained problems. (en)
foaf:isPrimaryTopicOf	http://en.wikipedia.org/wiki/Hybrid_algorithm_(constraint_satisfaction)
is Link from a Wikipage to another Wikipage of	Hybrid algorithm Constraint satisfaction problem
is foaf:primaryTopic of	http://en.wikipedia.org/wiki/Hybrid_algorithm_(constraint_satisfaction)

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