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