TY  - GEN
AU  - Richter,Urban Maximilian
TI  - Controlled self-organisation using learning classifier systems
SN  - KSP/1000013138
PY  - 2009///
PB  - KIT Scientific Publishing
KW  - organic computing
KW  - multi-agent simulation
KW  - controlled self-organisation
KW  - observer/controller architecture
KW  - extended learning classifier system
N1  - Open Access
N2  - 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
UR  - https://www.ksp.kit.edu/9783866444317
UR  - https://directory.doabooks.org/handle/20.500.12854/44037
ER  -