Core-guided minimal correction set and core enumeration

Nina Narodytska, Nikolaj Bjørner, Maria Cristina Marinescu, Mooly Sagiv

Producción científica: Capítulo del libroContribución a congreso/conferenciarevisión exhaustiva

34 Citas (Scopus)

Resumen

A set of constraints is unsatisfiable if there is no solution that satisfies these constraints. To analyse unsatisfiable problems, the user needs to understand where inconsistencies come from and how they can be repaired. Minimal unsatisfiable cores and correction sets are important subsets of constraints that enable such analysis. In this work, we propose a new algorithm for extracting minimal unsatisfiable cores and correction sets simultaneously. Building on top of the relaxation and strengthening framework, we introduce novel techniques for extracting these sets. Our new solver significantly outperforms several state of the art algorithms on common benchmarks when it comes to extracting correction sets and compares favorably on core extraction.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 27th International Joint Conference on Artificial Intelligence, IJCAI 2018
EditoresJerome Lang
EditorialInternational Joint Conferences on Artificial Intelligence
Páginas1353-1361
Número de páginas9
ISBN (versión digital)9780999241127
DOI
EstadoPublicada - 2018
Publicado de forma externa
Evento27th International Joint Conference on Artificial Intelligence, IJCAI 2018 - Stockholm, Suecia
Duración: 13 jul 201819 jul 2018

Serie de la publicación

NombreIJCAI International Joint Conference on Artificial Intelligence
Volumen2018-July
ISSN (versión impresa)1045-0823

Conferencia

Conferencia27th International Joint Conference on Artificial Intelligence, IJCAI 2018
País/TerritorioSuecia
CiudadStockholm
Período13/07/1819/07/18

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