Metabolic Systemic Computing: Exploiting Innate Immunity within an Artificial Organism for On-line Self-Organisation and Anomaly Detection |
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Authors: | Erwan Le Martelot Peter J Bentley |
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Institution: | (1) Engineering Department, University College London, London, UK;(2) Computer Science Department, University College London, London, UK |
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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. |
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Keywords: | Systemic computation Tissue Innate immunity Anomaly detection Self-organisation Danger theory Artificial organism Artificial metabolism Artificial immune system |
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