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...
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| Format: | Electronic Book Chapter |
| Language: | English |
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KIT Scientific Publishing
2009
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| Online Access: | DOAB: download the publication DOAB: description of the publication |
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| 020 | |a KSP/1000013138 | ||
| 020 | |a 9783866444317 | ||
| 040 | |a oapen |c oapen | ||
| 024 | 7 | |a 10.5445/KSP/1000013138 |c doi | |
| 041 | 0 | |a eng | |
| 042 | |a dc | ||
| 100 | 1 | |a Richter, Urban Maximilian |4 auth | |
| 245 | 1 | 0 | |a Controlled self-organisation using learning classifier systems |
| 260 | |b KIT Scientific Publishing |c 2009 | ||
| 300 | |a 1 electronic resource (XXV, 218 p. p.) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 520 | |a 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. | ||
| 540 | |a Creative Commons |f https://creativecommons.org/licenses/by-nc-nd/4.0/ |2 cc |4 https://creativecommons.org/licenses/by-nc-nd/4.0/ | ||
| 546 | |a English | ||
| 653 | |a organic computing | ||
| 653 | |a multi-agent simulation | ||
| 653 | |a controlled self-organisation | ||
| 653 | |a observer/controller architecture | ||
| 653 | |a extended learning classifier system | ||
| 856 | 4 | 0 | |a www.oapen.org |u https://www.ksp.kit.edu/9783866444317 |7 0 |z DOAB: download the publication |
| 856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/44037 |7 0 |z DOAB: description of the publication |