2007 IEEE Congress on Evolutionary Computation 2007
DOI: 10.1109/cec.2007.4425022
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Towards a Quantitative Notion of Self-organisation

Abstract: 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 … Show more

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Cited by 13 publications
(4 citation statements)
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“…Our distributed algorithm enables MIDs to selforganise their temporal calibration. Speaking in terms of selforganisation as defined by Cakar et al [21], we investigate self-organisation without central control. We define a fast and lightweight heuristic for visual saliency for mobile devices considering limited resources and allowing for real-time processing.…”
Section: Saliency Manager and Frame Synchronisation Algorithmmentioning
confidence: 99%
“…Our distributed algorithm enables MIDs to selforganise their temporal calibration. Speaking in terms of selforganisation as defined by Cakar et al [21], we investigate self-organisation without central control. We define a fast and lightweight heuristic for visual saliency for mobile devices considering limited resources and allowing for real-time processing.…”
Section: Saliency Manager and Frame Synchronisation Algorithmmentioning
confidence: 99%
“…Die im Forschungsgebiet Organic Computing [12] entwickelte generische Observer/ControllerArchitektur [2,13] …”
Section: Zusammenfassungunclassified
“…Jede der folgenden Untersuchungen wurde mindestens 25-mal durchgeführt und der Durchschnitt berechnet. Im rechten Teil von Abb 2. ist die Gesamtlastkurve für den Fall dargestellt, dass sich die Geräte und Anlagen untereinander abstimmen.…”
unclassified
“…The Observer is designed to monitor and analyze the SuOC in order to characterize the current system status, predict future states and identify possible emergent behavior that needs to be either interrupted or enforced. To some extent emergent behavior in self-organizing systems can be detected by quantitatively measuring statistical or entropy values of the analyzed data [4]. The task of the Controller is to influence the SuOC such that it exhibits the desired behavior as specified by the user.…”
Section: Observer/controller Architecturementioning
confidence: 99%