Richter, Urban Maximilian <br/><br/>
Controlled self-organisation using learning classifier systems 

 -  KIT Scientific Publishing  2009 
 - 1 electronic resource (XXV, 218 p. p.) 
<br/><br/> Open Access 
<br/><br/> 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. 
<br/><br/><br/>Creative Commons 
<br/><br/><br/>English 
<br/><br/><label>ISBN: </label>KSP/1000013138 9783866444317 
<br/><br/><label>Standard No.: </label>10.5445/KSP/1000013138  doi 
<br/><br/><label>Subjects--Index Terms: </label>organic computing multi-agent simulation controlled self-organisation observer/controller architecture extended learning classifier system