Controlled Self-Organisation Using Learning Classifier Systems (Repost)
Controlled Self-Organisation Using Learning Classifier Systems By Urban Maximilian Richter
2009 | 244 Pages | ISBN: 3866444311 | PDF | 66 MB
2009 | 244 Pages | ISBN: 3866444311 | PDF | 66 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