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Erschienen in:
2006 | OriginalPaper | Buchkapitel
On Permutation Masks in Hamming Negative Selection
verfasst von : Thomas Stibor, Jonathan Timmis, Claudia Eckert
Erschienen in: Artificial Immune Systems
Verlag: 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.