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dc.contributor.author
Alfano, Gianvincenzo  
dc.contributor.author
Greco, Sergio  
dc.contributor.author
Parisi, Francesco  
dc.contributor.author
Simari, Gerardo  
dc.contributor.author
Simari, Guillermo Ricardo  
dc.date.available
2021-09-24T13:21:11Z  
dc.date.issued
2021-11  
dc.identifier.citation
Alfano, Gianvincenzo; Greco, Sergio; Parisi, Francesco; Simari, Gerardo; Simari, Guillermo Ricardo; Incremental computation for structured argumentation over dynamic DeLP knowledge bases; Elsevier Science; Artificial Intelligence; 300; 11-2021; 1-30; 103553  
dc.identifier.issn
0004-3702  
dc.identifier.uri
http://hdl.handle.net/11336/141459  
dc.description.abstract
Structured argumentation systems, and their implementation, represent an important research subject in the area of Knowledge Representation and Reasoning. Structured argumentation advances over abstract argumentation frameworks by providing the internal construction of the arguments that are usually defined by a set of (strict and defeasible) rules. By considering the structure of arguments, it becomes possible to analyze reasons for and against a conclusion, and the warrant status of such a claim in the context of a knowledge base represents the main output of a dialectical process. Computing such statuses is a costly process, and any update to the knowledge base could potentially have a huge impact if done naively. In this work, we investigate the case of updates consisting of both additions and removals of pieces of knowledge in the Defeasible Logic Programming (DeLP) framework, first analyzing the complexity of the problem and then identifying conditions under which we can avoid unnecessary computations—central to this is the development of structures (e.g. graphs) to keep track of which results can potentially be affected by a given update. We introduce a technique for the incremental computation of the warrant statuses of conclusions in DeLP knowledge bases that evolve due to the application of (sets of) updates. We present the results of a thorough experimental evaluation showing that our incremental approach yields significantly faster running times in practice, as well as overall fewer recomputations, even in the case of sets of updates performed simultaneously.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Elsevier Science  
dc.rights
info:eu-repo/semantics/restrictedAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/  
dc.subject
DEFEASIBLE LOGIC PROGRAMMING  
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DYNAMIC DELP ARGUMENTATION  
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STRUCTURED ARGUMENTATION  
dc.subject.classification
Ciencias de la Computación  
dc.subject.classification
Ciencias de la Computación e Información  
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CIENCIAS NATURALES Y EXACTAS  
dc.title
Incremental computation for structured argumentation over dynamic DeLP knowledge bases  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2021-07-27T14:58:26Z  
dc.journal.volume
300  
dc.journal.pagination
1-30; 103553  
dc.journal.pais
Países Bajos  
dc.journal.ciudad
Amsterdam  
dc.description.fil
Fil: Alfano, Gianvincenzo. Università della Calabria; Italia  
dc.description.fil
Fil: Greco, Sergio. Università della Calabria; Italia  
dc.description.fil
Fil: Parisi, Francesco. Università della Calabria; Italia  
dc.description.fil
Fil: Simari, Gerardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina  
dc.description.fil
Fil: Simari, Guillermo Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina  
dc.journal.title
Artificial Intelligence  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0004370221001041  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.artint.2021.103553