INSPIRING FUTURES

An engineering-Informed modelling approach to AIS.

Hart, Emma and Davoudani, Despina (2011) An engineering-Informed modelling approach to AIS. In: Proceedings of International Conference on Artificial Immune Systems (ICARIS 2010). Lecture Notes in Computer Science . Springer-Verlag, pp. 240-253. ISBN 978-3-642-22370-9

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    Abstract/Description

    A recent shift in thinking in Artificial Immune Systems (AIS)
    advocates developing a greater understanding of the underlying biological
    systems that serve as inspiration for engineering such systems by
    developing abstract computational models of the immune system in order
    to better understand the natural biology. We propose a refinement
    to existing frameworks which requires development of such models to be
    driven by the engineering problem being considered; the constraints of
    the engineered system must inform not only the model development, but
    also its validation. Using a case-study, we present a methodology which
    enables an abstract model of dendritic-cell trafficking to be developed
    with the purpose of building a self-organising wireless sensor network for
    temperature monitoring and maintenance. The methodology enables the
    development of a model which is consistent with the application constraints
    from the outset and can be validated in terms of the functional
    requirements of the application. Although the result models are not likely
    to be biologically faithful, they enable the engineer to better exploit the
    underlying metaphor, ultimately leading to reduced development time of
    the engineered system.

    Item Type: Book Section
    ISBN: 978-3-642-22370-9
    Electronic ISBN: 978-3-642-22371-6
    Uncontrolled Keywords: Artificial Immune Systems; computational modelling;
    University Divisions/Research Centres: Edinburgh Napier University, Institute for Informatics and Digital Innovation
    Dewey Decimal Subjects: 000 Computer science, information & general works > 000 Computer science, knowledge & systems > 006 Special Computer Methods > 006.3 Artificial intelligence
    Library of Congress Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    Item ID: 4551
    Depositing User: Computing Research
    Date Deposited: 27 Jun 2011 12:04
    Last Modified: 22 Oct 2013 11:43
    URI: http://researchrepository.napier.ac.uk/id/eprint/4551

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