Integrating answer set programming and constraint logic programming
We introduce a knowledge representation language extending the syntax and semantics of ASP and CR-Prolog, give some examples of its use, and present an algorithm, , for computing answer sets of programs. The algorithm does not require full grounding of a program and combines “classical” ASP solving...
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Veröffentlicht in: | Annals of mathematics and artificial intelligence 2008-08, Vol.53 (1-4), p.251-287 |
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container_title | Annals of mathematics and artificial intelligence |
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creator | Mellarkod, Veena S. Gelfond, Michael Zhang, Yuanlin |
description | We introduce a knowledge representation language
extending the syntax and semantics of ASP and CR-Prolog, give some examples of its use, and present an algorithm,
, for computing answer sets of
programs. The algorithm does not require full grounding of a program and combines “classical” ASP solving methods with constraint logic programming techniques and CR-Prolog based abduction. The
based approach often allows to solve problems which are impossible to solve by more traditional ASP solving techniques. We believe that further investigation of the language and development of more efficient and reliable solvers for its programs can help to substantially expand the domain of applicability of the answer set programming paradigm. |
doi_str_mv | 10.1007/s10472-009-9116-y |
format | Article |
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extending the syntax and semantics of ASP and CR-Prolog, give some examples of its use, and present an algorithm,
, for computing answer sets of
programs. The algorithm does not require full grounding of a program and combines “classical” ASP solving methods with constraint logic programming techniques and CR-Prolog based abduction. The
based approach often allows to solve problems which are impossible to solve by more traditional ASP solving techniques. We believe that further investigation of the language and development of more efficient and reliable solvers for its programs can help to substantially expand the domain of applicability of the answer set programming paradigm.</description><identifier>ISSN: 1012-2443</identifier><identifier>EISSN: 1573-7470</identifier><identifier>DOI: 10.1007/s10472-009-9116-y</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Abduction ; Algorithms ; Artificial Intelligence ; Chromium ; Complex Systems ; Computer Science ; Declarative programming ; Expert systems ; Knowledge representation ; Logic programming ; Mathematical analysis ; Mathematical programming ; Mathematics ; Programming ; Prolog ; Semantics ; Solvers</subject><ispartof>Annals of mathematics and artificial intelligence, 2008-08, Vol.53 (1-4), p.251-287</ispartof><rights>Springer Science+Business Media B.V. 2009</rights><rights>Springer Science+Business Media B.V. 2009.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c391t-7841be3e02ec8b37de5bbbffb80c693198ef4ede016bab59a62d1e31c60c6b323</citedby><cites>FETCH-LOGICAL-c391t-7841be3e02ec8b37de5bbbffb80c693198ef4ede016bab59a62d1e31c60c6b323</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10472-009-9116-y$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2918195573?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,21388,27924,27925,33744,33745,41488,42557,43805,51319,64385,64387,64389,72469</link.rule.ids></links><search><creatorcontrib>Mellarkod, Veena S.</creatorcontrib><creatorcontrib>Gelfond, Michael</creatorcontrib><creatorcontrib>Zhang, Yuanlin</creatorcontrib><title>Integrating answer set programming and constraint logic programming</title><title>Annals of mathematics and artificial intelligence</title><addtitle>Ann Math Artif Intell</addtitle><description>We introduce a knowledge representation language
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, for computing answer sets of
programs. The algorithm does not require full grounding of a program and combines “classical” ASP solving methods with constraint logic programming techniques and CR-Prolog based abduction. The
based approach often allows to solve problems which are impossible to solve by more traditional ASP solving techniques. 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programs. The algorithm does not require full grounding of a program and combines “classical” ASP solving methods with constraint logic programming techniques and CR-Prolog based abduction. The
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subjects | Abduction Algorithms Artificial Intelligence Chromium Complex Systems Computer Science Declarative programming Expert systems Knowledge representation Logic programming Mathematical analysis Mathematical programming Mathematics Programming Prolog Semantics Solvers |
title | Integrating answer set programming and constraint logic programming |
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