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In this paper, we summarise the state of the art and introduce a definition of self-organisation that addresses the problem of designing self-organising technical systems, which is the main objective of the OC initiative.
 
In this paper, we summarise the state of the art and introduce a definition of self-organisation that addresses the problem of designing self-organising technical systems, which is the main objective of the OC initiative.
 
|ISBN=978-1-4244-1340-9
 
|ISBN=978-1-4244-1340-9
|Download=10.1109/CEC.2007.4425022
+
|DOI Name=10.1109/CEC.2007.4425022
 
|Projekt=OCCS, QE
 
|Projekt=OCCS, QE
 
|Forschungsgruppe=Effiziente Algorithmen
 
|Forschungsgruppe=Effiziente Algorithmen

Aktuelle Version vom 23. September 2009, 23:01 Uhr


Towards a Quantitative Notion of Self-Organisation


Towards a Quantitative Notion of Self-Organisation



Published: 2007 September

Buchtitel: Proceedings of the 2007 IEEE Congress on Evolutionary Computation (CEC 2007)
Seiten: 4222-4229

Referierte Veröffentlichung

BibTeX

Kurzfassung
Organic Computing (OC) and other research initiatives like Autonomic Computing or Proactive Computing have developed the idea of systems that possess life-like properties, that self-organise, that adapt to their dynamically changing environments, and that establish other so-called self-x properties, like self-healing, self-configuration, self-optimisation etc. What we are searching for in OC are not concepts for systems that simply self-organise, but systems that self-organise to achieve a well defined system goal. Therefore we talk in OC about controlled self-organisation.

Although the term self-organisation has been discussed for years, we miss a clear definition of self-organisation in most publications, which have a technically motivated background.

In this paper, we summarise the state of the art and introduce a definition of self-organisation that addresses the problem of designing self-organising technical systems, which is the main objective of the OC initiative.

ISBN: 978-1-4244-1340-9
DOI Link: 10.1109/CEC.2007.4425022

Projekt

OCCSQE



Forschungsgruppe

Effiziente Algorithmen


Forschungsgebiet

Organic Computing