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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/21439
Ver los metadatos del registro completo
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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 |
dc.date.none.fl_str_mv |
2003-05 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
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eng |
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eng |
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info:eu-repo/semantics/openAccess 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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openAccess |
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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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