Controlled self-organisation using learning classifier systems

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Controlled self-organisation using learning classifier systems

Richter, Urban Maximilian - Personal Name;

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.

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Series Title: -
Call Number: 005 RIC c
Publisher: : KIT Scientific Publishing., 2009
Collation: -
Language: English
ISBN/ISSN: 978-3-86644-431-7
Classification: 005
Content Type: text
Media Type: computer
Carrier Type: online resource
Edition: -
Subject(s): Computer Science
Specific Detail Info: -
Statement of Responsibility: Urban Maximilian Richter

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Cataloger: Erwin Hendarto
Source: -
Validator: maya

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