On the use of hyperspheres in artificial immune systems as antibody recognition regions

Thomas Stibor*, Jonathan Timmis, Claudia Eckert

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

38 Citations (SciVal)


Using hyperspheres as antibody recognition regions is an established abstraction which was initially proposed by theoretical immunologists for use in the modeling of antibody-antigen interactions. This abstraction is also employed in the development of many artificial immune system algorithms. Here, we show several undesirable properties of hyperspheres, especially when operating in high dimensions and discuss the problems of hyperspheres as recognition regions and how they have affected overall performance of certain algorithms in the context of real-valued negative selection.

Original languageEnglish
Title of host publicationArtificial Immune Systems - 5th International Conference, ICARIS 2006. Proceedings
EditorsHugues Bersini, Jorge Carneiro
PublisherSpringer Nature
Number of pages14
ISBN (Print)3540377492, 9783540377498
Publication statusPublished - 2006
Event5th International Conference on Artificial Immune Systems, ICARIS 2006 - Oeiras, Portugal
Duration: 04 Sept 200606 Sept 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4163 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference5th International Conference on Artificial Immune Systems, ICARIS 2006
Period04 Sept 200606 Sept 2006


  • false alarm rate
  • anomaly detection
  • repertoire size
  • Monte Carlo integration
  • unitary hypercube

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