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Frequency analysis for dendritic cell population tuning

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Abstract

The dendritic cell algorithm (DCA) has been applied successfully to a diverse range of applications. These applications are related by the inherent uncertainty associated with sensing the application environment. The DCA has performed well using unfiltered signals from each environment as inputs. In this paper we demonstrate that the DCA has an emergent filtering mechanism caused by the manner in which the cell accumulates its internal variables. Furthermore we demonstrate a relationship between the migration threshold of the cells and the transfer function of the algorithm. A tuning methodology is proposed and a robotic application published previously is revisited using the new tuning technique.

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Acknowledgments

The authors would like to thank Dr. Gordon Wyeth of the University of Queensland for his technical insight and support; William Wilson and Phil Birkin for their recommendations and suggestions throughout the derivation process and Heather Chapleo for her assistance during the practical experiments. This project is financially supported by MobileRobots Inc.

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Authors and Affiliations

  1. School of Computer Science, University of Nottingham, Jubilee Campus, Wollaton Road, Nottingham, NG8 1BB, UK

    Robert Oates, Graham Kendall & Jonathan M. Garibaldi

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  1. Robert Oates
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  2. Graham Kendall
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  3. Jonathan M. Garibaldi
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Correspondence to Robert Oates.

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Oates, R., Kendall, G. & Garibaldi, J.M. Frequency analysis for dendritic cell population tuning. Evol. Intel. 1, 145–157 (2008). https://doi.org/10.1007/s12065-008-0011-y

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  • DOI: https://doi.org/10.1007/s12065-008-0011-y

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