Combining quantitative and qualitative reasoning in defeasible argumentation

Autores
Chesñevar, Carlos Iván; Simari, Guillermo Ricardo
Año de publicación
2002
Idioma
español castellano
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Labeled Deductive Systems (LDS) were developed as a rigorous but exible method- ology to formalize complex logical systems, such as temporal logics, database query languages and defeasible reasoning systems. LDSAR is a LDS-based framework for defeasible argumentation which subsumes di erent existing argumentation frameworks, providing a testbed for the study of dif- ferent relevant features (such as logical properties and ontological aspects, among others). This paper presents LDS AR, an extension of LDSAR that incorporates the ability to combine quantitative and qualitative features within a uni ed argumentative setting. Our approach involves the assignment of certainty factors to formulas in the knowl- edge base. These values are propagated when performing argumentative inference, o ering an alternative source of information for evaluating the strength of arguments in the dialectical analysis. We will also discuss some emerging logical properties of the resulting framework.
Eje: Lógica e Inteligencia artificial
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Defeasible Argumentation
Quantitative Reasoning
Labelled Deductive Systems
ARTIFICIAL INTELLIGENCE
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:10915/23110
Acceder
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network_name_str SEDICI (UNLP)
spelling Combining quantitative and qualitative reasoning in defeasible argumentationChesñevar, Carlos IvánSimari, Guillermo RicardoCiencias InformáticasDefeasible ArgumentationQuantitative ReasoningLabelled Deductive SystemsARTIFICIAL INTELLIGENCELabeled Deductive Systems (LDS) were developed as a rigorous but exible method- ology to formalize complex logical systems, such as temporal logics, database query languages and defeasible reasoning systems. LDSAR is a LDS-based framework for defeasible argumentation which subsumes di erent existing argumentation frameworks, providing a testbed for the study of dif- ferent relevant features (such as logical properties and ontological aspects, among others). This paper presents LDS AR, an extension of LDSAR that incorporates the ability to combine quantitative and qualitative features within a uni ed argumentative setting. Our approach involves the assignment of certainty factors to formulas in the knowl- edge base. These values are propagated when performing argumentative inference, o ering an alternative source of information for evaluating the strength of arguments in the dialectical analysis. We will also discuss some emerging logical properties of the resulting framework.Eje: Lógica e Inteligencia artificialRed de Universidades con Carreras en Informática (RedUNCI)2002-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf272-283http://sedici.unlp.edu.ar/handle/10915/23110spainfo: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:UNLP2025-10-15T10:47:56Zoai:sedici.unlp.edu.ar:10915/23110Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 10:47:56.498SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Combining quantitative and qualitative reasoning in defeasible argumentation
title Combining quantitative and qualitative reasoning in defeasible argumentation
spellingShingle Combining quantitative and qualitative reasoning in defeasible argumentation
Chesñevar, Carlos Iván
Ciencias Informáticas
Defeasible Argumentation
Quantitative Reasoning
Labelled Deductive Systems
ARTIFICIAL INTELLIGENCE
title_short Combining quantitative and qualitative reasoning in defeasible argumentation
title_full Combining quantitative and qualitative reasoning in defeasible argumentation
title_fullStr Combining quantitative and qualitative reasoning in defeasible argumentation
title_full_unstemmed Combining quantitative and qualitative reasoning in defeasible argumentation
title_sort Combining quantitative and qualitative reasoning in defeasible argumentation
dc.creator.none.fl_str_mv Chesñevar, Carlos Iván
Simari, Guillermo Ricardo
author Chesñevar, Carlos Iván
author_facet Chesñevar, Carlos Iván
Simari, Guillermo Ricardo
author_role author
author2 Simari, Guillermo Ricardo
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Defeasible Argumentation
Quantitative Reasoning
Labelled Deductive Systems
ARTIFICIAL INTELLIGENCE
topic Ciencias Informáticas
Defeasible Argumentation
Quantitative Reasoning
Labelled Deductive Systems
ARTIFICIAL INTELLIGENCE
dc.description.none.fl_txt_mv Labeled Deductive Systems (LDS) were developed as a rigorous but exible method- ology to formalize complex logical systems, such as temporal logics, database query languages and defeasible reasoning systems. LDSAR is a LDS-based framework for defeasible argumentation which subsumes di erent existing argumentation frameworks, providing a testbed for the study of dif- ferent relevant features (such as logical properties and ontological aspects, among others). This paper presents LDS AR, an extension of LDSAR that incorporates the ability to combine quantitative and qualitative features within a uni ed argumentative setting. Our approach involves the assignment of certainty factors to formulas in the knowl- edge base. These values are propagated when performing argumentative inference, o ering an alternative source of information for evaluating the strength of arguments in the dialectical analysis. We will also discuss some emerging logical properties of the resulting framework.
Eje: Lógica e Inteligencia artificial
Red de Universidades con Carreras en Informática (RedUNCI)
description Labeled Deductive Systems (LDS) were developed as a rigorous but exible method- ology to formalize complex logical systems, such as temporal logics, database query languages and defeasible reasoning systems. LDSAR is a LDS-based framework for defeasible argumentation which subsumes di erent existing argumentation frameworks, providing a testbed for the study of dif- ferent relevant features (such as logical properties and ontological aspects, among others). This paper presents LDS AR, an extension of LDSAR that incorporates the ability to combine quantitative and qualitative features within a uni ed argumentative setting. Our approach involves the assignment of certainty factors to formulas in the knowl- edge base. These values are propagated when performing argumentative inference, o ering an alternative source of information for evaluating the strength of arguments in the dialectical analysis. We will also discuss some emerging logical properties of the resulting framework.
publishDate 2002
dc.date.none.fl_str_mv 2002-10
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info:eu-repo/semantics/publishedVersion
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dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/23110
url http://sedici.unlp.edu.ar/handle/10915/23110
dc.language.none.fl_str_mv spa
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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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rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
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272-283
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