On Permutation Masks in Hamming Negative Selection

نویسندگان

  • Thomas Stibor
  • Jonathan Timmis
  • Claudia Eckert
چکیده

Abstract. 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.

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تاریخ انتشار 2006