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Investigating the evolution and stability of a resource limited artificial immune system
Jon Timmis and Mark Neal
In A.S.Wu, editor, Special Workshop on Artificial Immune Systems, Gentic and Evolutionay Computtion Conference (GECCO) 2000, Workshop Program, pages 182-196, Las Vegas, Nevada, U.S.A., July 2000. AAAI, AAAI Press.Abstract
This paper presents a resource limited artificial immune system for data analysis. The work presented here builds upon previous work on artificial immune systems for data analysis. A population control mechanism, inspired by the natural immune system, has been introduced to control population growth and allow termination of the learning algorithm. The new algorithm is presented, along with the immunological metaphors used as inspiration. Results are presented for the Fisher Iris data set, where very successful results are obtained in identifying clusters within the data set. It is argued that this new resource based mechanism is a large step forward in making artificial immune systems a viable contender for effective unsupervised machine learning and allows for not just a one shot learning mechanism, but a continual learning model to be developed.
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Bibtex Record
@inproceedings{1063,
author = {Jon Timmis and Mark Neal},
title = {Investigating the evolution and stability of a resource limited artificial immune system},
month = {July},
year = {2000},
pages = {182-196},
keywords = {determinacy analysis, Craig interpolants},
note = {},
doi = {},
url = {http://www.cs.kent.ac.uk/pubs/2000/1063},
address = {Las Vegas, Nevada, U.S.A.},
booktitle = {Special Workshop on Artificial Immune Systems, Gentic and Evolutionay Computtion Conference (GECCO) 2000},
editor = {A.S.Wu},
organization = {AAAI},
publication_type = {inproceedings},
publisher = {AAAI Press},
refereed = {no},
series = {Workshop Program},
submission_id = {12613_963928766},
}