On the Use of Hyperspheres in Artificial Immune Systems as Antibody Recognition Regions

  • Thomas Stibor
  • Jonathan Timmis
  • Claudia Eckert
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4163)


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.


False Alarm Rate Anomaly Detection Repertoire Size Monte Carlo Integration Unitary Hypercube 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Thomas Stibor
    • 1
  • Jonathan Timmis
    • 2
  • Claudia Eckert
    • 1
  1. 1.Department of Computer ScienceDarmstadt University of Technology 
  2. 2.Departments of Electronics and Computer ScienceUniversity of YorkHeslington

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