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...
Bewaard in:
| Hoofdauteur: | |
|---|---|
| Formaat: | Elektronisch Hoofdstuk |
| Taal: | Engels |
| Gepubliceerd in: |
KIT Scientific Publishing
2009
|
| Onderwerpen: | |
| Online toegang: | DOAB: download the publication DOAB: description of the publication |
| Tags: |
Voeg label toe
Geen labels, Wees de eerste die dit record labelt!
|
| Samenvatting: | 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. |
|---|---|
| Fysieke beschrijving: | 1 electronic resource (XXV, 218 p. p.) |
| ISBN: | KSP/1000013138 9783866444317 |
| Toegang: | Open Access |