Mostrar o rexistro simple do ítem

dc.contributor.authorAguado, Felicidad
dc.contributor.authorCabalar, Pedro
dc.contributor.authorFandiño, Jorge
dc.contributor.authorPearce, David
dc.contributor.authorPérez, Gilberto
dc.contributor.authorVidal, Concepción
dc.date.accessioned2024-04-22T12:59:51Z
dc.date.available2024-04-22T12:59:51Z
dc.date.issued2024-01
dc.identifier.citationF. Aguado, P. Cabalar, J. Fandiño, D. Pearce, G. Pérez, and C. Vidal, "Syntactic ASP forgetting with forks", Artificial Intelligence, Vol. 326, 104033, Jan. 2024, doi: 10.1016/j.artint.2023.104033es_ES
dc.identifier.urihttp://hdl.handle.net/2183/36290
dc.description.abstract[Abstract]: Answer Set Programming (ASP) constitutes nowadays one of the most successful paradigms for practical Knowledge Representation and declarative problem solving. The formal analysis of ASP programs is essential for a rigorous treatment of specifications, the correct construction of solvers and the extension with other representational features. In this paper, we present a syntactic transformation, called the unfolding operator, that allows forgetting an atom in a logic program (under ASP semantics). The main advantage of unfolding is that, unlike other syntactic operators, it is always applicable and guarantees strong persistence, that is, the result preserves the same stable models with respect to any context where the forgotten atom does not occur. The price for its completeness is that the result is an expression that may contain the fork operator. Yet, we illustrate how, in some cases, the application of fork properties may allow us to reduce the fork to a logic program.es_ES
dc.description.sponsorshipWe want to thank the anonymous reviewers for their suggestions that helped to improve this paper. Partially funded by Regional Government of Galicia and the European Union, grants CITIC (ED431G 2019/01), GPC ED431B 2022/33, by the Spanish Ministry of Science and Innovation, Spain, MCIN/AEI/10.13039/501100011033 (grant PID2020-116201GB-I00), by BBVA Foundation, Scientific Research Grants, (project LIANDA), and by the National Science Foundation (NSF 95-3101-0060-402).es_ES
dc.description.sponsorshipXunta de Galicia; ED431G 2019/01es_ES
dc.description.sponsorshipXunta de Galicia; ED431B 2022/33es_ES
dc.description.sponsorshipUnited States. National Science Foundation; 95-3101-0060-402es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-116201GB-I00/ES/RAZONAMIENTO AUTOMATICO Y APRENDIZAJE CON INDUCCION DE CONOCIMIENTO/es_ES
dc.relation.urihttps://doi.org/10.1016/j.artint.2023.104033es_ES
dc.rightsAtribución 3.0 Españaes_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectAnswer set programminges_ES
dc.subjectEquilibrium logices_ES
dc.subjectForgetting; Forkses_ES
dc.subjectStrong equivalencees_ES
dc.subjectStrong persistencees_ES
dc.titleSyntactic ASP forgetting with forkses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleArtificial Intelligencees_ES
UDC.volume326es_ES
UDC.startPage104033es_ES
dc.identifier.doi10.1016/j.artint.2023.104033


Ficheiros no ítem

Thumbnail
Thumbnail

Este ítem aparece na(s) seguinte(s) colección(s)

Mostrar o rexistro simple do ítem