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Theoretical formulation and analysis of the deterministic dendritic cell algorithm.

Feng Gu1, Julie Greensmith, Uwe Aickelin

  • 1School of Computing, University of Leeds, LS2 9JT, UK. f.gu@leeds.ac.uk

Bio Systems
|January 23, 2013
PubMed
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The dendritic cell algorithm (DCA) is formally defined as dDCA, providing theoretical insights. Runtime analyses reveal the standard dDCA

Area of Science:

  • Artificial Immune Systems (AIS)
  • Computational Intelligence
  • Algorithm Analysis

Background:

  • The dendritic cell algorithm (DCA) is an emerging artificial immune system (AIS) algorithm.
  • Existing research primarily focuses on empirical aspects, lacking formal definition and theoretical analysis.
  • Ambiguity in understanding the DCA stems from its informal definition.

Purpose of the Study:

  • To provide a formal definition of the dendritic cell algorithm (DCA).
  • To conduct runtime analyses of the DCA and its segmented variant.
  • To reveal the theoretical aspects of the DCA through mathematical formulation.

Main Methods:

  • Formal definition of the deterministic DCA (dDCA) using set theory and mathematical functions.
  • Runtime analysis of the standard dDCA.

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  • Runtime analysis of the dDCA with added segmentation.
  • Formulation of runtime variables based on input data.

    • Main Results:

    • The standard dDCA exhibits a worst-case runtime complexity of O(n(2)).
    • Segmentation modifies the worst-case runtime complexity to O(max(nN,nz)).
    • Two runtime variables were formulated to guide further development.

    Conclusions:

    • The formal definition and runtime analysis of the dDCA address its theoretical underpinnings.
    • The study provides crucial insights into the computational complexity of the DCA.
    • Findings offer guidelines for optimizing the DCA's performance and future development.