Analyzing the defeat relation in observation-based defeasible logic programming

Autores
Capobianco, Marcela; Chesñevar, Carlos Iván; Simari, Guillermo Ricardo
Año de publicación
2004
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
In the last decade several ways to formalize defeasible reasoning have been studied. A particular approach, defeasible argumentation, has been particularly successful to achieve this goal. The inference process of argument-based systems is based on the interaction of ar- guments for and against certain conclusions. The relations of attack and defeat among arguments are key elements in these inference process. Usually a preference criterion is used to calculate the defeat relation to decide, in case of con ict, which argument is preferred over its contender. Speci city is a domain independent principle that has been used in several formalisms. In this work we analyze the problem of incorporating speci city to characterize defeat in a particular argumentative framework, called Observation Based Defeasible Logic Program- ming. Since e ciency is an important issue in ODeLP, we have devised a new version of this criterion, that optimizes the computation of the defeat relation. We also present a formal proof to show that this new version is equivalent to the old one.
Eje: V - Workshop de agentes y sistemas inteligentes
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
knowledge representation
ARTIFICIAL INTELLIGENCE
Intelligent agents
defeasible reasoning
argumentation
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/22519

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network_name_str SEDICI (UNLP)
spelling Analyzing the defeat relation in observation-based defeasible logic programmingCapobianco, MarcelaChesñevar, Carlos IvánSimari, Guillermo RicardoCiencias Informáticasknowledge representationARTIFICIAL INTELLIGENCEIntelligent agentsdefeasible reasoningargumentationIn the last decade several ways to formalize defeasible reasoning have been studied. A particular approach, defeasible argumentation, has been particularly successful to achieve this goal. The inference process of argument-based systems is based on the interaction of ar- guments for and against certain conclusions. The relations of attack and defeat among arguments are key elements in these inference process. Usually a preference criterion is used to calculate the defeat relation to decide, in case of con ict, which argument is preferred over its contender. Speci city is a domain independent principle that has been used in several formalisms. In this work we analyze the problem of incorporating speci city to characterize defeat in a particular argumentative framework, called Observation Based Defeasible Logic Program- ming. Since e ciency is an important issue in ODeLP, we have devised a new version of this criterion, that optimizes the computation of the defeat relation. We also present a formal proof to show that this new version is equivalent to the old one.Eje: V - Workshop de agentes y sistemas inteligentesRed de Universidades con Carreras en Informática (RedUNCI)2004info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/22519enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:27:53Zoai:sedici.unlp.edu.ar:10915/22519Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:27:53.772SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Analyzing the defeat relation in observation-based defeasible logic programming
title Analyzing the defeat relation in observation-based defeasible logic programming
spellingShingle Analyzing the defeat relation in observation-based defeasible logic programming
Capobianco, Marcela
Ciencias Informáticas
knowledge representation
ARTIFICIAL INTELLIGENCE
Intelligent agents
defeasible reasoning
argumentation
title_short Analyzing the defeat relation in observation-based defeasible logic programming
title_full Analyzing the defeat relation in observation-based defeasible logic programming
title_fullStr Analyzing the defeat relation in observation-based defeasible logic programming
title_full_unstemmed Analyzing the defeat relation in observation-based defeasible logic programming
title_sort Analyzing the defeat relation in observation-based defeasible logic programming
dc.creator.none.fl_str_mv Capobianco, Marcela
Chesñevar, Carlos Iván
Simari, Guillermo Ricardo
author Capobianco, Marcela
author_facet Capobianco, Marcela
Chesñevar, Carlos Iván
Simari, Guillermo Ricardo
author_role author
author2 Chesñevar, Carlos Iván
Simari, Guillermo Ricardo
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
knowledge representation
ARTIFICIAL INTELLIGENCE
Intelligent agents
defeasible reasoning
argumentation
topic Ciencias Informáticas
knowledge representation
ARTIFICIAL INTELLIGENCE
Intelligent agents
defeasible reasoning
argumentation
dc.description.none.fl_txt_mv In the last decade several ways to formalize defeasible reasoning have been studied. A particular approach, defeasible argumentation, has been particularly successful to achieve this goal. The inference process of argument-based systems is based on the interaction of ar- guments for and against certain conclusions. The relations of attack and defeat among arguments are key elements in these inference process. Usually a preference criterion is used to calculate the defeat relation to decide, in case of con ict, which argument is preferred over its contender. Speci city is a domain independent principle that has been used in several formalisms. In this work we analyze the problem of incorporating speci city to characterize defeat in a particular argumentative framework, called Observation Based Defeasible Logic Program- ming. Since e ciency is an important issue in ODeLP, we have devised a new version of this criterion, that optimizes the computation of the defeat relation. We also present a formal proof to show that this new version is equivalent to the old one.
Eje: V - Workshop de agentes y sistemas inteligentes
Red de Universidades con Carreras en Informática (RedUNCI)
description In the last decade several ways to formalize defeasible reasoning have been studied. A particular approach, defeasible argumentation, has been particularly successful to achieve this goal. The inference process of argument-based systems is based on the interaction of ar- guments for and against certain conclusions. The relations of attack and defeat among arguments are key elements in these inference process. Usually a preference criterion is used to calculate the defeat relation to decide, in case of con ict, which argument is preferred over its contender. Speci city is a domain independent principle that has been used in several formalisms. In this work we analyze the problem of incorporating speci city to characterize defeat in a particular argumentative framework, called Observation Based Defeasible Logic Program- ming. Since e ciency is an important issue in ODeLP, we have devised a new version of this criterion, that optimizes the computation of the defeat relation. We also present a formal proof to show that this new version is equivalent to the old one.
publishDate 2004
dc.date.none.fl_str_mv 2004
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/22519
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dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
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