2006 | OriginalPaper | Chapter
On Permutation Masks in Hamming Negative Selection
Authors : Thomas Stibor, Jonathan Timmis, Claudia Eckert
Published in: Artificial Immune Systems
Publisher: Springer Berlin Heidelberg
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Permutation masks were proposed for reducing the number of holes in Hamming negative selection when applying the
r
-contiguous or
r
-chunk matching rule. Here, we show that (randomly determined) permutation masks re-arrange the semantic representation of the underlying data and therefore shatter self-regions. As a consequence, detectors do not cover areas around self regions, instead they cover randomly distributed elements across the space. In addition, we observe that the resulting holes occur in regions where actually no self regions should occur.