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Controlled self-organisation using learning classifier systems - Urban Maximilian Richter

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2014-08-13
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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 ... Visas aprašymas

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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.

Daugiau informacijos

Autorius Urban Maximilian Richter
Leidėjas Karlsruher Institut für Technologie
Išleidimo metai 2014
Viršelio tipas Minkšti viršeliai
EAN 9783866444317
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36,17 € 48,22 €