Research Output

Exploiting the analogy between immunology and sparse distributed memory.

  The relationship between immunological memory and a class of associative memories known as sparse distributed memories (SDM) is well known. This paper proposes a new model for clustering non-stationary data based on a combination of salient features from the two metaphors. The resulting system embodies the important principles of both types of memory; it is self-organising, robust, scalable, dynamic and can perform anomaly detection. The model is rst applied to clustering static datasets, and is shown to outperform two other systems based on immunological principles. It is then applied to clustering non-stationary data-sets with promising results.

  • Date:

    30 November 2001

  • Publication Status:

    Published

  • Publisher

    University of Kent at Canterbury Printing Unit

  • Library of Congress:

    QA75 Electronic computers. Computer science

  • Dewey Decimal Classification:

    006.3 Artificial intelligence

Citation

Hart, E. & Ross, P. (2001). Exploiting the analogy between immunology and sparse distributed memory. In Timmis, J. & Bentley, P. (Eds.). 1st International Conference on Artificial Immune Systems, 59-67. ISBN 1-902671-32-5

Authors

Keywords

Immunology; sparse distributed computing; clustering; non-stationery data;

Available Documents