What Have Gene Libraries Done for AIS?

  • Steve Cayzer
  • Jim Smith
  • James A. R. Marshall
  • Tim Kovacs
Conference paper

DOI: 10.1007/11536444_7

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3627)
Cite this paper as:
Cayzer S., Smith J., Marshall J.A.R., Kovacs T. (2005) What Have Gene Libraries Done for AIS?. In: Jacob C., Pilat M.L., Bentley P.J., Timmis J.I. (eds) Artificial Immune Systems. ICARIS 2005. Lecture Notes in Computer Science, vol 3627. Springer, Berlin, Heidelberg

Abstract

Artificial Immune Systems (AIS) have been shown to be useful, practical and realisable approaches to real-world problems. Most AIS implementations are based around a canonical algorithm such as clonotypic learning, which we may think of as individual, lifetime learning. Yet a species also learns. Gene libraries are often thought of as a biological mechanism for generating combinatorial diversity of antibodies. However, they also bias the antibody creation process, so that they can be viewed as a way of guiding the lifetime learning mechanisms. Over time, the gene libraries in a species will evolve to an appropriate bias for the expected environment (based on species memory). Thus gene libraries are a form of meta-learning which could be useful for AIS. Yet they are hardly ever used. In this paper we consider some of the possible benefits and implications of incorporating the evolution of gene libraries into AIS practice. We examine some of the issues that must be considered if the implementation is to be successful and beneficial.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Steve Cayzer
    • 1
  • Jim Smith
    • 2
  • James A. R. Marshall
    • 3
  • Tim Kovacs
    • 3
  1. 1.HP LaboratoriesBristolUK
  2. 2.Faculty of Computing Engineering and Mathematical SciencesUniversity of the West of EnglandBristolUK
  3. 3.Department of Computer ScienceUniversity of BristolBristolUK

Personalised recommendations