Metabolic Systemic Computing: Exploiting Innate Immunity within an Artificial Organism for On-line Self-Organisation and Anomaly Detection

Article

Abstract

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.

Keywords

Systemic computation Tissue Innate immunity Anomaly detection Self-organisation Danger theory Artificial organism Artificial metabolism Artificial immune system 

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Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  1. 1.Engineering DepartmentUniversity College LondonLondonUK
  2. 2.Computer Science DepartmentUniversity College LondonLondonUK

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