Revisions of orders in dynamic systems

Autores
Falappa, Marcelo Alejandro; Simari, Patricio D.
Año de publicación
2001
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Current reasoning systems attempt to model an agent's knowledge and interaction with its environment in a symbolic manner. This environment, its world is generally dynamic and changing due to natural evolution or the actions of other agents that are a part of it. In consequence, an agent that is a part of a reasoning system must have the following components: a knowledge base where its knowledge of the world is stored, a communication mechanism with the environment and other agents in it, and a means of modifying its knowledge of the environment. Knowledge may be represented by a logic language which is propositional, first order, modal or extentions of these. Each one of these alternatives has advantages as well as disadvantages. The higher the expressive power of a given language, the more computational problems there are regarding complexity and decidability. Communication mechanisms can be varied, depending on the environment being modeled. They can be multimedia mechanisms such as microphones, speakers, video cameras, infrared sensors, motion detectors and even wired or wireless systems where information is transmitted without any kind of preprocessing. They are irrelevant, however, for the purpose of our research because we are focused in the development of the knowledge system. Mechanisms for modifying knowledge may be modeled by what is known as Belief Change Theory. Belief Change Theory assumes that the underlying language is at least propositional. An agent's knowledge is represented as a set of sentences and new information as a single sentence. In turn, every change operator takes a set of sentences and a single sentence and produces a new set of sentences as a result.
Eje: Inteligencia Artificial Distribuida, Aspectos Teóricos de la Inteligencia Artificial y Teoría de la Computación
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
ARTIFICIAL INTELLIGENCE
Revisions of Orders
Theory of Computation
Dynamic Systems
Distributed Systems
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:10915/21645

id SEDICI_48f93f4a1f1fc047c90ff3517a258f23
oai_identifier_str oai:sedici.unlp.edu.ar:10915/21645
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Revisions of orders in dynamic systemsFalappa, Marcelo AlejandroSimari, Patricio D.Ciencias InformáticasARTIFICIAL INTELLIGENCERevisions of OrdersTheory of ComputationDynamic SystemsDistributed SystemsCurrent reasoning systems attempt to model an agent's knowledge and interaction with its environment in a symbolic manner. This environment, its world is generally dynamic and changing due to natural evolution or the actions of other agents that are a part of it. In consequence, an agent that is a part of a reasoning system must have the following components: a knowledge base where its knowledge of the world is stored, a communication mechanism with the environment and other agents in it, and a means of modifying its knowledge of the environment. Knowledge may be represented by a logic language which is propositional, first order, modal or extentions of these. Each one of these alternatives has advantages as well as disadvantages. The higher the expressive power of a given language, the more computational problems there are regarding complexity and decidability. Communication mechanisms can be varied, depending on the environment being modeled. They can be multimedia mechanisms such as microphones, speakers, video cameras, infrared sensors, motion detectors and even wired or wireless systems where information is transmitted without any kind of preprocessing. They are irrelevant, however, for the purpose of our research because we are focused in the development of the knowledge system. Mechanisms for modifying knowledge may be modeled by what is known as Belief Change Theory. Belief Change Theory assumes that the underlying language is at least propositional. An agent's knowledge is represented as a set of sentences and new information as a single sentence. In turn, every change operator takes a set of sentences and a single sentence and produces a new set of sentences as a result.Eje: Inteligencia Artificial Distribuida, Aspectos Teóricos de la Inteligencia Artificial y Teoría de la ComputaciónRed de Universidades con Carreras en Informática (RedUNCI)2001-05info: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/10915/21645enginfo: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:UNLP2025-09-29T10:54:43Zoai:sedici.unlp.edu.ar:10915/21645Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:54:43.273SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Revisions of orders in dynamic systems
title Revisions of orders in dynamic systems
spellingShingle Revisions of orders in dynamic systems
Falappa, Marcelo Alejandro
Ciencias Informáticas
ARTIFICIAL INTELLIGENCE
Revisions of Orders
Theory of Computation
Dynamic Systems
Distributed Systems
title_short Revisions of orders in dynamic systems
title_full Revisions of orders in dynamic systems
title_fullStr Revisions of orders in dynamic systems
title_full_unstemmed Revisions of orders in dynamic systems
title_sort Revisions of orders in dynamic systems
dc.creator.none.fl_str_mv Falappa, Marcelo Alejandro
Simari, Patricio D.
author Falappa, Marcelo Alejandro
author_facet Falappa, Marcelo Alejandro
Simari, Patricio D.
author_role author
author2 Simari, Patricio D.
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
ARTIFICIAL INTELLIGENCE
Revisions of Orders
Theory of Computation
Dynamic Systems
Distributed Systems
topic Ciencias Informáticas
ARTIFICIAL INTELLIGENCE
Revisions of Orders
Theory of Computation
Dynamic Systems
Distributed Systems
dc.description.none.fl_txt_mv Current reasoning systems attempt to model an agent's knowledge and interaction with its environment in a symbolic manner. This environment, its world is generally dynamic and changing due to natural evolution or the actions of other agents that are a part of it. In consequence, an agent that is a part of a reasoning system must have the following components: a knowledge base where its knowledge of the world is stored, a communication mechanism with the environment and other agents in it, and a means of modifying its knowledge of the environment. Knowledge may be represented by a logic language which is propositional, first order, modal or extentions of these. Each one of these alternatives has advantages as well as disadvantages. The higher the expressive power of a given language, the more computational problems there are regarding complexity and decidability. Communication mechanisms can be varied, depending on the environment being modeled. They can be multimedia mechanisms such as microphones, speakers, video cameras, infrared sensors, motion detectors and even wired or wireless systems where information is transmitted without any kind of preprocessing. They are irrelevant, however, for the purpose of our research because we are focused in the development of the knowledge system. Mechanisms for modifying knowledge may be modeled by what is known as Belief Change Theory. Belief Change Theory assumes that the underlying language is at least propositional. An agent's knowledge is represented as a set of sentences and new information as a single sentence. In turn, every change operator takes a set of sentences and a single sentence and produces a new set of sentences as a result.
Eje: Inteligencia Artificial Distribuida, Aspectos Teóricos de la Inteligencia Artificial y Teoría de la Computación
Red de Universidades con Carreras en Informática (RedUNCI)
description Current reasoning systems attempt to model an agent's knowledge and interaction with its environment in a symbolic manner. This environment, its world is generally dynamic and changing due to natural evolution or the actions of other agents that are a part of it. In consequence, an agent that is a part of a reasoning system must have the following components: a knowledge base where its knowledge of the world is stored, a communication mechanism with the environment and other agents in it, and a means of modifying its knowledge of the environment. Knowledge may be represented by a logic language which is propositional, first order, modal or extentions of these. Each one of these alternatives has advantages as well as disadvantages. The higher the expressive power of a given language, the more computational problems there are regarding complexity and decidability. Communication mechanisms can be varied, depending on the environment being modeled. They can be multimedia mechanisms such as microphones, speakers, video cameras, infrared sensors, motion detectors and even wired or wireless systems where information is transmitted without any kind of preprocessing. They are irrelevant, however, for the purpose of our research because we are focused in the development of the knowledge system. Mechanisms for modifying knowledge may be modeled by what is known as Belief Change Theory. Belief Change Theory assumes that the underlying language is at least propositional. An agent's knowledge is represented as a set of sentences and new information as a single sentence. In turn, every change operator takes a set of sentences and a single sentence and produces a new set of sentences as a result.
publishDate 2001
dc.date.none.fl_str_mv 2001-05
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
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/21645
url http://sedici.unlp.edu.ar/handle/10915/21645
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv 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)
eu_rights_str_mv openAccess
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)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
_version_ 1844615805115826176
score 13.070432