Evolution of neurocontrollers in changing environments

Autores
Apolloni, Javier; Kavka, Carlos; Roggero, Patricia
Año de publicación
2002
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
One of the most challenging aspects of the control theory is the design and implementation of controllers that can deal with changing environments, i. e., non stationary systems. Quite good progress has been made on this area by using different kind of models: neural networks, fuzzy systems, evolutionary algorithms, etc. Our approach consists in the use of a memory based evolutionary algorithm, specially designed in such a way that can be used to evolve neurocontrollers to be applied in changing environments. In this paper, we describe our architecture, and present an example of its application to a typical control problem.
Eje: Sistemas inteligentes
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
evolutionary algorithms
neural networks
control
Algorithms
Neural nets
Environments
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:10915/23039
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/23039
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Evolution of neurocontrollers in changing environmentsApolloni, JavierKavka, CarlosRoggero, PatriciaCiencias Informáticasevolutionary algorithmsneural networkscontrolAlgorithmsNeural netsEnvironmentsARTIFICIAL INTELLIGENCEOne of the most challenging aspects of the control theory is the design and implementation of controllers that can deal with changing environments, i. e., non stationary systems. Quite good progress has been made on this area by using different kind of models: neural networks, fuzzy systems, evolutionary algorithms, etc. Our approach consists in the use of a memory based evolutionary algorithm, specially designed in such a way that can be used to evolve neurocontrollers to be applied in changing environments. In this paper, we describe our architecture, and present an example of its application to a typical control problem.Eje: Sistemas inteligentesRed 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/pdf32-43http://sedici.unlp.edu.ar/handle/10915/23039enginfo: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:UNLP2025-09-03T10:28:07Zoai:sedici.unlp.edu.ar:10915/23039Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:28:07.365SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Evolution of neurocontrollers in changing environments
title Evolution of neurocontrollers in changing environments
spellingShingle Evolution of neurocontrollers in changing environments
Apolloni, Javier
Ciencias Informáticas
evolutionary algorithms
neural networks
control
Algorithms
Neural nets
Environments
ARTIFICIAL INTELLIGENCE
title_short Evolution of neurocontrollers in changing environments
title_full Evolution of neurocontrollers in changing environments
title_fullStr Evolution of neurocontrollers in changing environments
title_full_unstemmed Evolution of neurocontrollers in changing environments
title_sort Evolution of neurocontrollers in changing environments
dc.creator.none.fl_str_mv Apolloni, Javier
Kavka, Carlos
Roggero, Patricia
author Apolloni, Javier
author_facet Apolloni, Javier
Kavka, Carlos
Roggero, Patricia
author_role author
author2 Kavka, Carlos
Roggero, Patricia
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
evolutionary algorithms
neural networks
control
Algorithms
Neural nets
Environments
ARTIFICIAL INTELLIGENCE
topic Ciencias Informáticas
evolutionary algorithms
neural networks
control
Algorithms
Neural nets
Environments
ARTIFICIAL INTELLIGENCE
dc.description.none.fl_txt_mv One of the most challenging aspects of the control theory is the design and implementation of controllers that can deal with changing environments, i. e., non stationary systems. Quite good progress has been made on this area by using different kind of models: neural networks, fuzzy systems, evolutionary algorithms, etc. Our approach consists in the use of a memory based evolutionary algorithm, specially designed in such a way that can be used to evolve neurocontrollers to be applied in changing environments. In this paper, we describe our architecture, and present an example of its application to a typical control problem.
Eje: Sistemas inteligentes
Red de Universidades con Carreras en Informática (RedUNCI)
description One of the most challenging aspects of the control theory is the design and implementation of controllers that can deal with changing environments, i. e., non stationary systems. Quite good progress has been made on this area by using different kind of models: neural networks, fuzzy systems, evolutionary algorithms, etc. Our approach consists in the use of a memory based evolutionary algorithm, specially designed in such a way that can be used to evolve neurocontrollers to be applied in changing environments. In this paper, we describe our architecture, and present an example of its application to a typical control problem.
publishDate 2002
dc.date.none.fl_str_mv 2002-10
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/10915/23039
url http://sedici.unlp.edu.ar/handle/10915/23039
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
32-43
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
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score 13.13397

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