Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14365/3980
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Akgun O. | - |
dc.contributor.author | Miguel I. | - |
dc.contributor.author | Jefferson C. | - |
dc.contributor.author | Frisch A.M. | - |
dc.contributor.author | Hnich B. | - |
dc.date.accessioned | 2023-06-16T15:06:33Z | - |
dc.date.available | 2023-06-16T15:06:33Z | - |
dc.date.issued | 2011 | - |
dc.identifier.isbn | 9.78158E+12 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14365/3980 | - |
dc.description | Association for the Advancement of Artificial Intelligence (AAAI);National Science Foundation;AI Journal;Google, Inc.;Microsoft Research | en_US |
dc.description | 25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference, AAAI-11 / IAAI-11 -- 7 August 2011 through 11 August 2011 -- San Francisco, CA -- 87049 | en_US |
dc.description.abstract | In constraint solving, a critical bottleneck is the formulation of an effective constraint model of a given problem. The CONJURE system described in this paper, a substantial step forward over prototype versions of CONJURE previously reported, makes a valuable contribution to the automation of constraint modelling by automatically producing constraint models from their specifications in the abstract constraint specification language ESSENCE. A set of rules is used to refine an abstract specification into a concrete constraint model. We demonstrate that this set of rules is readily extensible to increase the space of possible constraint models CONJURE can produce. Our empirical results confirm that CONJURE can reproduce successfully the kernels of the constraint models of 32 benchmark problems found in the literature. Copyright © 2011, Association for the Advancement of Artificial Intelligence. All rights reserved. | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | Proceedings of the National Conference on Artificial Intelligence | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Abstract specifications | en_US |
dc.subject | Bench-mark problems | en_US |
dc.subject | Constraint model | en_US |
dc.subject | Constraint modelling | en_US |
dc.subject | Constraint Solving | en_US |
dc.subject | Constraint specification languages | en_US |
dc.subject | Empirical results | en_US |
dc.subject | Prototype versions | en_US |
dc.subject | Set of rules | en_US |
dc.subject | Abstracting | en_US |
dc.subject | Specification languages | en_US |
dc.subject | Specifications | en_US |
dc.subject | Artificial intelligence | en_US |
dc.title | Extensible automated constraint modelling | en_US |
dc.type | Conference Object | en_US |
dc.identifier.scopus | 2-s2.0-80055050149 | en_US |
dc.authorscopusid | 53979404400 | - |
dc.authorscopusid | 56232171100 | - |
dc.authorscopusid | 7005590984 | - |
dc.authorscopusid | 6602458958 | - |
dc.identifier.volume | 1 | en_US |
dc.identifier.startpage | 4 | en_US |
dc.identifier.endpage | 11 | en_US |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.identifier.scopusquality | N/A | - |
dc.identifier.wosquality | N/A | - |
item.grantfulltext | reserved | - |
item.openairetype | Conference Object | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.fulltext | With Fulltext | - |
item.languageiso639-1 | en | - |
item.cerifentitytype | Publications | - |
Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
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File | Size | Format | |
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3007.pdf Restricted Access | 161.15 kB | Adobe PDF | View/Open Request a copy |
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