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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Main Author: Richter, Urban Maximilian (auth)
Format: Book Chapter
Published: KIT Scientific Publishing 2009
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DOAB: description of the publication
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001 doab_20_500_12854_44037
005 20210211
020 |a KSP/1000013138 
020 |a 9783866444317 
024 7 |a 10.5445/KSP/1000013138  |c doi 
041 0 |a English 
042 |a dc 
100 1 |a Richter, Urban Maximilian  |4 auth 
245 1 0 |a Controlled self-organisation using learning classifier systems 
260 |b KIT Scientific Publishing  |c 2009 
300 |a 1 electronic resource (XXV, 218 p. p.) 
506 0 |a Open Access  |2 star  |f Unrestricted online access 
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. 
540 |a Creative Commons  |f https://creativecommons.org/licenses/by-nc-nd/4.0/  |2 cc  |4 https://creativecommons.org/licenses/by-nc-nd/4.0/ 
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 
856 4 0 |a www.oapen.org  |u https://www.ksp.kit.edu/9783866444317  |7 0  |z Get Fullteks 
856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/44037  |7 0  |z DOAB: description of the publication