A Possibilistic Defeasible Logic Programming Approach to Argumentation-Based Decision Making

Autores
Ferretti, Edgardo; Errecalde, Marcelo; Garcia, Alejandro Javier; Simari, Guillermo Ricardo
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The development of symbolic approaches to decision-making has become an evergrowing research line in artificial intelligence; argumentation has contributed to that with its unique strengths. Following this trend, this article proposes a general-purpose decision framework based on argumentation. Given a set of alternatives posed to the decisionmaker, the framework represents the agent’s preferences and knowledge by an epistemic component developed using possibilistic defeasible logic programming. The reasons by which a particular alternative is deemed better than another are explicitly considered in the argumentation process involved in warranting information from the epistemic component. The information warranted by the dialectical process is then used in decision rules that implement the agent’s general decision-making policy. Essentially, decision rules establish patterns of behaviour of the agent specifying under which conditions a set of alternatives will be considered acceptable; moreover, a methodology for programming the agent’s epistemic component is defined. It is demonstrated that programming the agent’s epistemic component following this methodology exhibits some interesting properties with respect to the selected alternatives; also, when all the relevantinformation regarding the agent’s preferences is specified, its choice behaviour coincides with respect to the optimum preference derived from a rational preference relation.
Fil: Ferretti, Edgardo. Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Departamento de Informática. Laboratorio Investigación y Desarrollo en Inteligencia Computacional; Argentina
Fil: Errecalde, Marcelo . Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Departamento de Informática. Laboratorio Investigación y Desarrollo en Inteligencia Computacional; Argentina
Fil: Garcia, Alejandro Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahia Blanca; Argentina. Universidad Nacional del Sur; Argentina
Fil: Simari, Guillermo Ricardo. Universidad Nacional del Sur; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahia Blanca; Argentina
Materia
Non-Monotonic Reasoning
Argumentation
Possibilistic Defeasible Logic
Programming
Decision Making
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/12390
Acceder
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network_name_str CONICET Digital (CONICET)
spelling A Possibilistic Defeasible Logic Programming Approach to Argumentation-Based Decision MakingFerretti, EdgardoErrecalde, Marcelo Garcia, Alejandro JavierSimari, Guillermo RicardoNon-Monotonic ReasoningArgumentationPossibilistic Defeasible LogicProgrammingDecision Makinghttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1The development of symbolic approaches to decision-making has become an evergrowing research line in artificial intelligence; argumentation has contributed to that with its unique strengths. Following this trend, this article proposes a general-purpose decision framework based on argumentation. Given a set of alternatives posed to the decisionmaker, the framework represents the agent’s preferences and knowledge by an epistemic component developed using possibilistic defeasible logic programming. The reasons by which a particular alternative is deemed better than another are explicitly considered in the argumentation process involved in warranting information from the epistemic component. The information warranted by the dialectical process is then used in decision rules that implement the agent’s general decision-making policy. Essentially, decision rules establish patterns of behaviour of the agent specifying under which conditions a set of alternatives will be considered acceptable; moreover, a methodology for programming the agent’s epistemic component is defined. It is demonstrated that programming the agent’s epistemic component following this methodology exhibits some interesting properties with respect to the selected alternatives; also, when all the relevantinformation regarding the agent’s preferences is specified, its choice behaviour coincides with respect to the optimum preference derived from a rational preference relation.Fil: Ferretti, Edgardo. Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Departamento de Informática. Laboratorio Investigación y Desarrollo en Inteligencia Computacional; ArgentinaFil: Errecalde, Marcelo . Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Departamento de Informática. Laboratorio Investigación y Desarrollo en Inteligencia Computacional; ArgentinaFil: Garcia, Alejandro Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahia Blanca; Argentina. Universidad Nacional del Sur; ArgentinaFil: Simari, Guillermo Ricardo. Universidad Nacional del Sur; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahia Blanca; ArgentinaTaylor & Francis2014-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/12390Ferretti, Edgardo; Errecalde, Marcelo ; Garcia, Alejandro Javier; Simari, Guillermo Ricardo; A Possibilistic Defeasible Logic Programming Approach to Argumentation-Based Decision Making; Taylor & Francis; Journal Of Experimental And Theoretical Artificial Intelligence; 26; 4; 6-2014; 519-5500952-813Xenginfo:eu-repo/semantics/altIdentifier/url/http://www.tandfonline.com/doi/abs/10.1080/0952813X.2014.921733info:eu-repo/semantics/altIdentifier/doi/10.1080/0952813X.2014.921733info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:52:23Zoai:ri.conicet.gov.ar:11336/12390instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:52:23.894CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A Possibilistic Defeasible Logic Programming Approach to Argumentation-Based Decision Making
title A Possibilistic Defeasible Logic Programming Approach to Argumentation-Based Decision Making
spellingShingle A Possibilistic Defeasible Logic Programming Approach to Argumentation-Based Decision Making
Ferretti, Edgardo
Non-Monotonic Reasoning
Argumentation
Possibilistic Defeasible Logic
Programming
Decision Making
title_short A Possibilistic Defeasible Logic Programming Approach to Argumentation-Based Decision Making
title_full A Possibilistic Defeasible Logic Programming Approach to Argumentation-Based Decision Making
title_fullStr A Possibilistic Defeasible Logic Programming Approach to Argumentation-Based Decision Making
title_full_unstemmed A Possibilistic Defeasible Logic Programming Approach to Argumentation-Based Decision Making
title_sort A Possibilistic Defeasible Logic Programming Approach to Argumentation-Based Decision Making
dc.creator.none.fl_str_mv Ferretti, Edgardo
Errecalde, Marcelo
Garcia, Alejandro Javier
Simari, Guillermo Ricardo
author Ferretti, Edgardo
author_facet Ferretti, Edgardo
Errecalde, Marcelo
Garcia, Alejandro Javier
Simari, Guillermo Ricardo
author_role author
author2 Errecalde, Marcelo
Garcia, Alejandro Javier
Simari, Guillermo Ricardo
author2_role author
author
author
dc.subject.none.fl_str_mv Non-Monotonic Reasoning
Argumentation
Possibilistic Defeasible Logic
Programming
Decision Making
topic Non-Monotonic Reasoning
Argumentation
Possibilistic Defeasible Logic
Programming
Decision Making
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The development of symbolic approaches to decision-making has become an evergrowing research line in artificial intelligence; argumentation has contributed to that with its unique strengths. Following this trend, this article proposes a general-purpose decision framework based on argumentation. Given a set of alternatives posed to the decisionmaker, the framework represents the agent’s preferences and knowledge by an epistemic component developed using possibilistic defeasible logic programming. The reasons by which a particular alternative is deemed better than another are explicitly considered in the argumentation process involved in warranting information from the epistemic component. The information warranted by the dialectical process is then used in decision rules that implement the agent’s general decision-making policy. Essentially, decision rules establish patterns of behaviour of the agent specifying under which conditions a set of alternatives will be considered acceptable; moreover, a methodology for programming the agent’s epistemic component is defined. It is demonstrated that programming the agent’s epistemic component following this methodology exhibits some interesting properties with respect to the selected alternatives; also, when all the relevantinformation regarding the agent’s preferences is specified, its choice behaviour coincides with respect to the optimum preference derived from a rational preference relation.
Fil: Ferretti, Edgardo. Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Departamento de Informática. Laboratorio Investigación y Desarrollo en Inteligencia Computacional; Argentina
Fil: Errecalde, Marcelo . Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Departamento de Informática. Laboratorio Investigación y Desarrollo en Inteligencia Computacional; Argentina
Fil: Garcia, Alejandro Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahia Blanca; Argentina. Universidad Nacional del Sur; Argentina
Fil: Simari, Guillermo Ricardo. Universidad Nacional del Sur; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahia Blanca; Argentina
description The development of symbolic approaches to decision-making has become an evergrowing research line in artificial intelligence; argumentation has contributed to that with its unique strengths. Following this trend, this article proposes a general-purpose decision framework based on argumentation. Given a set of alternatives posed to the decisionmaker, the framework represents the agent’s preferences and knowledge by an epistemic component developed using possibilistic defeasible logic programming. The reasons by which a particular alternative is deemed better than another are explicitly considered in the argumentation process involved in warranting information from the epistemic component. The information warranted by the dialectical process is then used in decision rules that implement the agent’s general decision-making policy. Essentially, decision rules establish patterns of behaviour of the agent specifying under which conditions a set of alternatives will be considered acceptable; moreover, a methodology for programming the agent’s epistemic component is defined. It is demonstrated that programming the agent’s epistemic component following this methodology exhibits some interesting properties with respect to the selected alternatives; also, when all the relevantinformation regarding the agent’s preferences is specified, its choice behaviour coincides with respect to the optimum preference derived from a rational preference relation.
publishDate 2014
dc.date.none.fl_str_mv 2014-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/12390
Ferretti, Edgardo; Errecalde, Marcelo ; Garcia, Alejandro Javier; Simari, Guillermo Ricardo; A Possibilistic Defeasible Logic Programming Approach to Argumentation-Based Decision Making; Taylor & Francis; Journal Of Experimental And Theoretical Artificial Intelligence; 26; 4; 6-2014; 519-550
0952-813X
url http://hdl.handle.net/11336/12390
identifier_str_mv Ferretti, Edgardo; Errecalde, Marcelo ; Garcia, Alejandro Javier; Simari, Guillermo Ricardo; A Possibilistic Defeasible Logic Programming Approach to Argumentation-Based Decision Making; Taylor & Francis; Journal Of Experimental And Theoretical Artificial Intelligence; 26; 4; 6-2014; 519-550
0952-813X
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.tandfonline.com/doi/abs/10.1080/0952813X.2014.921733
info:eu-repo/semantics/altIdentifier/doi/10.1080/0952813X.2014.921733
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Taylor & Francis
publisher.none.fl_str_mv Taylor & Francis
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.069144

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