Controlled self-organisation using learning classifier systems
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 architect...
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| Year of Publication: | 2009 |
| Language: | English |
| Physical Description: | 1 electronic resource (XXV, 218 p. p.) |
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| 100 | 1 | |a Richter, Urban Maximilian |4 auth | |
| 245 | 1 | 0 | |a Controlled self-organisation using learning classifier systems |
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| 300 | |a 1 electronic resource (XXV, 218 p. p.) | ||
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| 520 | |a 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. | ||
| 546 | |a English | ||
| 653 | |a organic computing | ||
| 653 | |a multi-agent simulation | ||
| 653 | |a controlled self-organisation | ||
| 653 | |a observer/controller architecture | ||
| 653 | |a extended learning classifier system | ||
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| ADM | |b 2023-12-15 05:48:39 Europe/Vienna |f system |c marc21 |a 2019-11-10 04:18:40 Europe/Vienna |g false | ||
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