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− | |Title=Adaptivity and Self- | + | |Title=Adaptivity and Self-Organisation in Organic Computing Systems |
|Year=2010 | |Year=2010 | ||
|Month=September | |Month=September | ||
− | |Journal= | + | |Journal=ACM Transactions on Autonomous and Adaptive Systems (TAAS) |
|Volume=5 | |Volume=5 | ||
|Number=3 | |Number=3 | ||
− | |Pages=10:1 - 10:32 | + | |Pages=10:1-10:32 |
− | |Publisher= | + | |Publisher=ACM |
+ | |Address=New York, NY, USA | ||
}} | }} | ||
{{Publikation Details | {{Publikation Details | ||
− | |Projekt=OCCS | + | |Abstract=Organic Computing (OC) and other research initiatives like Autonomic Computing or Proactive Computing have developed the vision of systems possessing life-like properties: They self-organise, adapt to their dynamically changing environments, and establish other so-called self-x-properties, like self-healing, self-configuration, self-optimisation, etc. What we are searching for in OC are methodologies and concepts for systems that allow to cope with increasingly complex networked application systems by introduction of self-x-properties and at the same time guarantee a trustworthy and adaptive response to externally provided system objectives and control actions. Therefore, in OC, we talk about controlled self-organisation. |
+ | |||
+ | Although the terms self-organisation and adaptivity have been discussed for years, we miss a clear definition of self-organisation in most publications, which have a technically motivated background. | ||
+ | |||
+ | In this article, we briefly summarise the state of the art and suggest a characterisation of (controlled) self-organisation and adaptivity that is motivated by the main objectives of the OC initiative. We present a system classification of robust, adaptable, and adaptive systems and define a degree of autonomy to be able to quantify how autonomously a system is working. The degree of autonomy distinguishes and measures external control that is exerted directly by the user (no autonomy) from internal control of a system which might be fully controlled by an observer/controller architecture that is part of the system (full autonomy). The quantitative degree of autonomy provides the basis for characterising the notion of controlled self-organisation. Furthermore, we discuss several alternatives for the design of organic systems. | ||
+ | |ISSN=1556-4665 | ||
+ | |DOI Name=10.1145/1837909.1837911 | ||
+ | |Projekt=OCCS, QE | ||
|Forschungsgruppe=Effiziente Algorithmen | |Forschungsgruppe=Effiziente Algorithmen | ||
+ | }} | ||
+ | {{Forschungsgebiet Auswahl | ||
+ | |Forschungsgebiet=Organic Computing | ||
}} | }} |
Aktuelle Version vom 26. Mai 2011, 18:50 Uhr
Adaptivity and Self-Organisation in Organic Computing Systems
Adaptivity and Self-Organisation in Organic Computing Systems
Veröffentlicht: 2010 September
Erscheinungsort: New York, NY, USA
Journal: ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Nummer: 3
Seiten: 10:1-10:32
Verlag: ACM
Volume: 5
Referierte Veröffentlichung
Kurzfassung
Organic Computing (OC) and other research initiatives like Autonomic Computing or Proactive Computing have developed the vision of systems possessing life-like properties: They self-organise, adapt to their dynamically changing environments, and establish other so-called self-x-properties, like self-healing, self-configuration, self-optimisation, etc. What we are searching for in OC are methodologies and concepts for systems that allow to cope with increasingly complex networked application systems by introduction of self-x-properties and at the same time guarantee a trustworthy and adaptive response to externally provided system objectives and control actions. Therefore, in OC, we talk about controlled self-organisation.
Although the terms self-organisation and adaptivity have been discussed for years, we miss a clear definition of self-organisation in most publications, which have a technically motivated background.
In this article, we briefly summarise the state of the art and suggest a characterisation of (controlled) self-organisation and adaptivity that is motivated by the main objectives of the OC initiative. We present a system classification of robust, adaptable, and adaptive systems and define a degree of autonomy to be able to quantify how autonomously a system is working. The degree of autonomy distinguishes and measures external control that is exerted directly by the user (no autonomy) from internal control of a system which might be fully controlled by an observer/controller architecture that is part of the system (full autonomy). The quantitative degree of autonomy provides the basis for characterising the notion of controlled self-organisation. Furthermore, we discuss several alternatives for the design of organic systems.
ISSN: 1556-4665
DOI Link: 10.1145/1837909.1837911