School of Computing

A Multi-layerd Immune Inspired Machine Learning Algorithm

T. Knight and J. Timmis

In A. Lotfi and M. Garibaldi, editors, Applications and Science in Soft Computing, pages 182-196. Springer, December 2003.


Artificial Immune Systems (AIS) have recently been proposed as an additional soft computing paradigm. This paper proposes a new multi-layered unsupervised machine learning algorithm inspired by the vertebrate immune system. The algorithm has been tested on benchmark data and has shown a great deal of potential for data reduction and clustering tasks. This paper presents an overview of the algorithm, drawing analogies to the vertebrae immune system where appropriate. Results are presented for three data sets and observations are made about the potential for adapting the algorithm for a continuous learning paradigm.

Bibtex Record

author = {Knight, T. and Timmis, J.},
title = {{A Multi-layerd Immune Inspired Machine Learning Algorithm}},
month = {December},
year = {2003},
pages = {182-196},
keywords = {determinacy analysis, Craig interpolants},
note = {},
doi = {},
url = {},
    publication_type = {incollection},
    submission_id = {18036_1071827245},
    booktitle = {Applications and Science in Soft Computing},
    publisher = {Springer},
    editor = {Lotfi, A. and Garibaldi, M.},

School of Computing, University of Kent, Canterbury, Kent, CT2 7NF

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Last Updated: 21/03/2014