Non prioritized reasoning in intelligent agents

Autores
Falappa, Marcelo Alejandro; Simari, Guillermo Ricardo
Año de publicación
2003
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
The design of intelligent agents is greatly influenced by the many different models that exist to represent knowledge. It is essential that such agents have computationally adequate mechanisms to manage its knowledge, which more often than not is incomplete and/or inconsistent. It is also important for an agent to be able to obtain new conclusions that allow it to reason about the state of the world in which it is embedded. It has been proven that this problem cannot be solved within the realm of Classic Logic. This situation has triggered the development of a series of logical formalisms that extend the classic ones. These proposals often carry the names of Nonmonotonic Reasoning, or Defeasible Reasoning. Some examples of such models are McDermott and Doyle’s Nonmonotonic Logics, Reiter’s Default Logic, Moore’s Autoepistemic Logic, McCarthy’s Circumscription Model, and Belief Revision (also called Belief Change). This last formalism was introduced by G¨ardenfors and later extended by Alchourrón, G¨ardenfors, and Makinson [1, 4]
Eje: Inteligencia artificial
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
ARTIFICIAL INTELLIGENCE
Prioritized Reasoning
Intelligent agents
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:10915/21439

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network_name_str SEDICI (UNLP)
spelling Non prioritized reasoning in intelligent agentsFalappa, Marcelo AlejandroSimari, Guillermo RicardoCiencias InformáticasARTIFICIAL INTELLIGENCEPrioritized ReasoningIntelligent agentsThe design of intelligent agents is greatly influenced by the many different models that exist to represent knowledge. It is essential that such agents have computationally adequate mechanisms to manage its knowledge, which more often than not is incomplete and/or inconsistent. It is also important for an agent to be able to obtain new conclusions that allow it to reason about the state of the world in which it is embedded. It has been proven that this problem cannot be solved within the realm of Classic Logic. This situation has triggered the development of a series of logical formalisms that extend the classic ones. These proposals often carry the names of Nonmonotonic Reasoning, or Defeasible Reasoning. Some examples of such models are McDermott and Doyle’s Nonmonotonic Logics, Reiter’s Default Logic, Moore’s Autoepistemic Logic, McCarthy’s Circumscription Model, and Belief Revision (also called Belief Change). This last formalism was introduced by G¨ardenfors and later extended by Alchourrón, G¨ardenfors, and Makinson [1, 4]Eje: Inteligencia artificialRed de Universidades con Carreras en Informática (RedUNCI)2003-05info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf188-191http://sedici.unlp.edu.ar/handle/10915/21439enginfo: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:UNLP2025-09-03T10:27:26Zoai:sedici.unlp.edu.ar:10915/21439Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:27:26.971SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Non prioritized reasoning in intelligent agents
title Non prioritized reasoning in intelligent agents
spellingShingle Non prioritized reasoning in intelligent agents
Falappa, Marcelo Alejandro
Ciencias Informáticas
ARTIFICIAL INTELLIGENCE
Prioritized Reasoning
Intelligent agents
title_short Non prioritized reasoning in intelligent agents
title_full Non prioritized reasoning in intelligent agents
title_fullStr Non prioritized reasoning in intelligent agents
title_full_unstemmed Non prioritized reasoning in intelligent agents
title_sort Non prioritized reasoning in intelligent agents
dc.creator.none.fl_str_mv Falappa, Marcelo Alejandro
Simari, Guillermo Ricardo
author Falappa, Marcelo Alejandro
author_facet Falappa, Marcelo Alejandro
Simari, Guillermo Ricardo
author_role author
author2 Simari, Guillermo Ricardo
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
ARTIFICIAL INTELLIGENCE
Prioritized Reasoning
Intelligent agents
topic Ciencias Informáticas
ARTIFICIAL INTELLIGENCE
Prioritized Reasoning
Intelligent agents
dc.description.none.fl_txt_mv The design of intelligent agents is greatly influenced by the many different models that exist to represent knowledge. It is essential that such agents have computationally adequate mechanisms to manage its knowledge, which more often than not is incomplete and/or inconsistent. It is also important for an agent to be able to obtain new conclusions that allow it to reason about the state of the world in which it is embedded. It has been proven that this problem cannot be solved within the realm of Classic Logic. This situation has triggered the development of a series of logical formalisms that extend the classic ones. These proposals often carry the names of Nonmonotonic Reasoning, or Defeasible Reasoning. Some examples of such models are McDermott and Doyle’s Nonmonotonic Logics, Reiter’s Default Logic, Moore’s Autoepistemic Logic, McCarthy’s Circumscription Model, and Belief Revision (also called Belief Change). This last formalism was introduced by G¨ardenfors and later extended by Alchourrón, G¨ardenfors, and Makinson [1, 4]
Eje: Inteligencia artificial
Red de Universidades con Carreras en Informática (RedUNCI)
description The design of intelligent agents is greatly influenced by the many different models that exist to represent knowledge. It is essential that such agents have computationally adequate mechanisms to manage its knowledge, which more often than not is incomplete and/or inconsistent. It is also important for an agent to be able to obtain new conclusions that allow it to reason about the state of the world in which it is embedded. It has been proven that this problem cannot be solved within the realm of Classic Logic. This situation has triggered the development of a series of logical formalisms that extend the classic ones. These proposals often carry the names of Nonmonotonic Reasoning, or Defeasible Reasoning. Some examples of such models are McDermott and Doyle’s Nonmonotonic Logics, Reiter’s Default Logic, Moore’s Autoepistemic Logic, McCarthy’s Circumscription Model, and Belief Revision (also called Belief Change). This last formalism was introduced by G¨ardenfors and later extended by Alchourrón, G¨ardenfors, and Makinson [1, 4]
publishDate 2003
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dc.language.none.fl_str_mv eng
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