Le Martelot, E;
Metabolic systemic computing: Exploiting innate immunity within an artificial organism for on-line self-organisation and anomaly detection.
Journal of Mathematical Modelling and Algorithms
Previous work suggests that innate immunity and representations of tissue can be useful when combined with artificial immune systems. Here we provide a new implementation of tissue for artificial immune systems using systemic computation, a new model of computation and corresponding computer architecture based on a systemics world-view and supplemented by the incorporation of natural characteristics. We show using systemic computation how to create an artificial organism, a program with metabolism that eats data, expels waste, self-organise cells based on the nature of its food and emits danger signals suitable for an artificial immune system. The implementation is tested by application to two standard machine learning sets and shows excellent abilities to recognise anomalies in its diet as well as a consistent datawise self-organisation. © 2009 Springer Science+Business Media B.V.
|Title:||Metabolic systemic computing: Exploiting innate immunity within an artificial organism for on-line self-organisation and anomaly detection|
|Keywords:||Anomaly detection, Artificial immune system, Artificial metabolism, Artificial organism, Danger theory, Innate immunity, Self-organisation, Systemic computation, Tissue|
|UCL classification:||UCL > School of BEAMS > Faculty of Engineering Science
UCL > School of BEAMS > Faculty of Engineering Science > Computer Science
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