Controlled self-organisation using learning classifier systems By Urban M. Richter
Publisher: Unive rsität Karl sruhe Universitäts bibliothek 2009 | 248 Pages | ISBN: 3866444311 | PDF | 53 MB
Publisher: Unive rsität Karl sruhe Universitäts bibliothek 2009 | 248 Pages | ISBN: 3866444311 | PDF | 53 MB
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.
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