A Randomized Real-Valued Negative Selection Algorithm View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2003

AUTHORS

Fabio González , Dipankar Dasgupta , Luis Fernando Niño

ABSTRACT

This paper presents a real-valued negative selection algorithm with good mathematical foundation that solves some of the drawbacks of our previous approach [11]. Specifically, it can produce a good estimate of the optimal number of detectors needed to cover the non-self space, and the maximization of the non-self coverage is done through an optimization algorithm with proven convergence properties. The proposed method is a randomized algorithm based on Monte Carlo methods. Experiments are performed to validate the assumptions made while designing the algorithm and to evaluate its performance. More... »

PAGES

261-272

References to SciGraph publications

  • 2003-06-18. The Effect of Binary Matching Rules in Negative Selection in GENETIC AND EVOLUTIONARY COMPUTATION — GECCO 2003
  • Book

    TITLE

    Artificial Immune Systems

    ISBN

    978-3-540-40766-9
    978-3-540-45192-1

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-540-45192-1_25

    DOI

    http://dx.doi.org/10.1007/978-3-540-45192-1_25

    DIMENSIONS

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