Controlled self-organisation using learning classifier systems
The complexity of technical systems increases, breakdowns occur quite often. The mission of organic computing is to tame these challenges by providing degrees of freedom for self-organised behaviour. To achieve these goals, new methods have to be developed. The proposed observer/controller architect...
- Autores:
- Tipo de recurso:
- Book
- Fecha de publicación:
- 2019
- Institución:
- Universidad de Bogotá Jorge Tadeo Lozano
- Repositorio:
- Expeditio: repositorio UTadeo
- Idioma:
- eng
- OAI Identifier:
- oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/16662
- Palabra clave:
- Informática
Sistema de clasificación del aprendizaje extendido
Simulación de múltiples agentes
Informática orgánica
Controlled self-organisation
- Rights
- License
- Abierto (Texto Completo)
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oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/16662 |
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UTADEO2 |
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|
| dc.title.spa.fl_str_mv |
Controlled self-organisation using learning classifier systems |
| title |
Controlled self-organisation using learning classifier systems |
| spellingShingle |
Controlled self-organisation using learning classifier systems Informática Sistema de clasificación del aprendizaje extendido Simulación de múltiples agentes Informática orgánica Controlled self-organisation |
| title_short |
Controlled self-organisation using learning classifier systems |
| title_full |
Controlled self-organisation using learning classifier systems |
| title_fullStr |
Controlled self-organisation using learning classifier systems |
| title_full_unstemmed |
Controlled self-organisation using learning classifier systems |
| title_sort |
Controlled self-organisation using learning classifier systems |
| dc.subject.spa.fl_str_mv |
Informática |
| topic |
Informática Sistema de clasificación del aprendizaje extendido Simulación de múltiples agentes Informática orgánica Controlled self-organisation |
| dc.subject.lemb.spa.fl_str_mv |
Sistema de clasificación del aprendizaje extendido Simulación de múltiples agentes Informática orgánica |
| dc.subject.keyword.spa.fl_str_mv |
Controlled self-organisation |
| description |
The complexity of technical systems increases, breakdowns occur quite often. The mission of organic computing is to tame these challenges by providing degrees of freedom for self-organised behaviour. To achieve these goals, new methods have to be developed. The proposed observer/controller architecture constitutes one way to achieve controlled self-organisation. To improve its design, multi-agent scenarios are investigated. Especially, learning using learning classifier systems is addressed. |
| publishDate |
2019 |
| dc.date.created.none.fl_str_mv |
2019-07-30 |
| dc.date.accessioned.none.fl_str_mv |
2021-01-15T20:53:50Z |
| dc.date.available.none.fl_str_mv |
2021-01-15T20:53:50Z |
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http://purl.org/coar/resource_type/c_2f33 |
| format |
http://purl.org/coar/resource_type/c_2f33 |
| dc.identifier.isbn.none.fl_str_mv |
978-3-86644-431-7 |
| dc.identifier.other.none.fl_str_mv |
https://www.ksp.kit.edu/9783866444317 |
| dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/20.500.12010/16662 |
| dc.identifier.doi.none.fl_str_mv |
10.5445/KSP/1000013138 |
| identifier_str_mv |
978-3-86644-431-7 10.5445/KSP/1000013138 |
| url |
https://www.ksp.kit.edu/9783866444317 http://hdl.handle.net/20.500.12010/16662 |
| dc.language.iso.spa.fl_str_mv |
eng |
| language |
eng |
| dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
| dc.rights.local.spa.fl_str_mv |
Abierto (Texto Completo) |
| dc.rights.creativecommons.none.fl_str_mv |
https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode |
| rights_invalid_str_mv |
Abierto (Texto Completo) https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode http://purl.org/coar/access_right/c_abf2 |
| dc.format.extent.spa.fl_str_mv |
248 páginas |
| dc.format.mimetype.spa.fl_str_mv |
application/pdf |
| dc.publisher.spa.fl_str_mv |
KIT Scientific Publishing |
| institution |
Universidad de Bogotá Jorge Tadeo Lozano |
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expeditio@utadeo.edu.co |
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2021-01-15T20:53:50Z2021-01-15T20:53:50Z2019-07-30978-3-86644-431-7https://www.ksp.kit.edu/9783866444317http://hdl.handle.net/20.500.12010/1666210.5445/KSP/1000013138248 páginasapplication/pdfengKIT Scientific PublishingInformáticaSistema de clasificación del aprendizaje extendidoSimulación de múltiples agentesInformática orgánicaControlled self-organisationControlled self-organisation using learning classifier systemsAbierto (Texto Completo)https://creativecommons.org/licenses/by-nc-nd/4.0/legalcodehttp://purl.org/coar/access_right/c_abf2The complexity of technical systems increases, breakdowns occur quite often. The mission of organic computing is to tame these challenges by providing degrees of freedom for self-organised behaviour. To achieve these goals, new methods have to be developed. The proposed observer/controller architecture constitutes one way to achieve controlled self-organisation. To improve its design, multi-agent scenarios are investigated. Especially, learning using learning classifier systems is addressed.http://purl.org/coar/resource_type/c_2f33Richter, Urban MaximilianORIGINALControlled self-organisation using learning classifier systems_1.pdfControlled self-organisation using learning classifier systems_1.pdfVer documentoapplication/pdf69092368https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/16662/1/Controlled%20self-organisation%20using%20learning%20classifier%20systems_1.pdfa87ed92a30a72baa5d1e004adf77ea50MD51open accessLICENSElicense.txtlicense.txttext/plain; charset=utf-82938https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/16662/2/license.txtabceeb1c943c50d3343516f9dbfc110fMD52open accessTHUMBNAILControlled self-organisation using learning classifier systems_1.pdf.jpgControlled self-organisation using learning classifier systems_1.pdf.jpgIM Thumbnailimage/jpeg18582https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/16662/3/Controlled%20self-organisation%20using%20learning%20classifier%20systems_1.pdf.jpg39e70da4d261eb3fdc560369e9c49eb8MD53open access20.500.12010/16662oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/166622021-01-15 16:54:42.364open accessRepositorio Institucional - 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