Generating hard SAT/CSP instances using expander graphs

In this paper we provide a new method to generate hard k-SAT instances. We incrementally construct a high girth bipartite incidence graph of the k-SAT instance. Having high girth assures high expansion for the graph, and high expansion implies high resolution width. We have extended this approach to...

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Detalhes bibliográficos
Autores: Ansótegui Gil, Carlos José, Béjar Torres, Ramón, Fernàndez Camon, César, Mateu Piñol, Carles
Formato: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2008
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10459.1/46644
Acesso em linha:http://hdl.handle.net/10459.1/46644
Access Level:acceso abierto
Palavra-chave:Intel·ligència artificial
Tecnologia Innovacions
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spelling Generating hard SAT/CSP instances using expander graphsAnsótegui Gil, Carlos JoséBéjar Torres, RamónFernàndez Camon, CésarMateu Piñol, CarlesIntel·ligència artificialTecnologia InnovacionsIn this paper we provide a new method to generate hard k-SAT instances. We incrementally construct a high girth bipartite incidence graph of the k-SAT instance. Having high girth assures high expansion for the graph, and high expansion implies high resolution width. We have extended this approach to generate hard n-ary CSP instances and we have also adapted this idea to increase the expansion of the system of linear equations used to generate XORSAT instances, being able to produce harder satisfiable instances than former generators.Association for the Advancement of Artificial Intelligence2008info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionhttp://hdl.handle.net/10459.1/46644reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésVersió postprint del document publicat a: http://www.aaai.orgProceedings of the twenty-third National Conference on Artificial Intelligence, 2008, p. 1442-1443(c) Association for the Advancement of Artificial Intelligence, 2008info:eu-repo/semantics/openAccessoai:recercat.cat:10459.1/466442026-05-29T05:05:01Z
dc.title.none.fl_str_mv Generating hard SAT/CSP instances using expander graphs
title Generating hard SAT/CSP instances using expander graphs
spellingShingle Generating hard SAT/CSP instances using expander graphs
Ansótegui Gil, Carlos José
Intel·ligència artificial
Tecnologia Innovacions
title_short Generating hard SAT/CSP instances using expander graphs
title_full Generating hard SAT/CSP instances using expander graphs
title_fullStr Generating hard SAT/CSP instances using expander graphs
title_full_unstemmed Generating hard SAT/CSP instances using expander graphs
title_sort Generating hard SAT/CSP instances using expander graphs
dc.creator.none.fl_str_mv Ansótegui Gil, Carlos José
Béjar Torres, Ramón
Fernàndez Camon, César
Mateu Piñol, Carles
author Ansótegui Gil, Carlos José
author_facet Ansótegui Gil, Carlos José
Béjar Torres, Ramón
Fernàndez Camon, César
Mateu Piñol, Carles
author_role author
author2 Béjar Torres, Ramón
Fernàndez Camon, César
Mateu Piñol, Carles
author2_role author
author
author
dc.subject.none.fl_str_mv Intel·ligència artificial
Tecnologia Innovacions
topic Intel·ligència artificial
Tecnologia Innovacions
description In this paper we provide a new method to generate hard k-SAT instances. We incrementally construct a high girth bipartite incidence graph of the k-SAT instance. Having high girth assures high expansion for the graph, and high expansion implies high resolution width. We have extended this approach to generate hard n-ary CSP instances and we have also adapted this idea to increase the expansion of the system of linear equations used to generate XORSAT instances, being able to produce harder satisfiable instances than former generators.
publishDate 2008
dc.date.none.fl_str_mv 2008
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10459.1/46644
url http://hdl.handle.net/10459.1/46644
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Versió postprint del document publicat a: http://www.aaai.org
Proceedings of the twenty-third National Conference on Artificial Intelligence, 2008, p. 1442-1443
dc.rights.none.fl_str_mv (c) Association for the Advancement of Artificial Intelligence, 2008
info:eu-repo/semantics/openAccess
rights_invalid_str_mv (c) Association for the Advancement of Artificial Intelligence, 2008
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Association for the Advancement of Artificial Intelligence
publisher.none.fl_str_mv Association for the Advancement of Artificial Intelligence
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812429

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