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 ... Full description
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Description
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.
More Information
| Author | Urban Maximilian Richter |
|---|---|
| Publisher | Karlsruher Institut für Technologie |
| Release year | 2014 |
| Cover type | Softcover |
| EAN | 9783866444317 |