Abstract
This paper presents the inception and subsequent revisions of an immune-inspired supervised learning algorithm, Artificial Immune Recognition System (AIRS). It presents the immunological components that inspired the algorithm and describes the initial algorithm in detail. The discussion then moves to revisions of the basic algorithm that remove certain unnecessary complications of the original version. Experimental results for both versions of the algorithm are discussed and these results indicate that the revisions to the algorithm do not sacrifice accuracy while increasing the data reduction capabilities of AIRS.
Similar content being viewed by others
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Watkins, A., Timmis, J. & Boggess, L. Artificial Immune Recognition System (AIRS): An Immune-Inspired Supervised Learning Algorithm. Genet Program Evolvable Mach 5, 291–317 (2004). https://doi.org/10.1023/B:GENP.0000030197.83685.94
Issue Date:
DOI: https://doi.org/10.1023/B:GENP.0000030197.83685.94