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Artificial immune systems in the context of autonomic computing: integrating design paradigms

Published: 12 July 2014 Publication History

Abstract

We describe a design paradigm for developing autonomic computing systems based on an analogy with the natural immune system, and show how current approaches to designing autonomic systems could be enriched by considering alternative design processes based on cognitive immune networks.

References

[1]
N. Capodieci, E. Hart, and G. Cabri. An immune network approach for self-adaptive ensembles of autonomic components: a case study in swarm robotics. In Advances in Artificial Life, ECAL, volume 12, pages 864--871, 2013.
[2]
I. Cohen. Tending adam's garden: evolving the cognitive immune self. In Elsevier Academic Press, 2004.
[3]
P. Horn. Autonomic computing: Ibm's perspective on the state of information technology. IBM press, 2001.
[4]
J. Kephart and D. Chess. The vision of autonomic computing. Computer, 36(1):41--50, 2003.

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  • (2015)Lifelong Learning Selection Hyper-heuristics for Constraint Satisfaction ProblemsAdvances in Artificial Intelligence and Soft Computing10.1007/978-3-319-27060-9_15(190-201)Online publication date: 30-Dec-2015

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  1. Artificial immune systems in the context of autonomic computing: integrating design paradigms

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    cover image ACM Conferences
    GECCO Comp '14: Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation
    July 2014
    1524 pages
    ISBN:9781450328814
    DOI:10.1145/2598394
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    New York, NY, United States

    Publication History

    Published: 12 July 2014

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    Author Tags

    1. artificial immune systems
    2. autonomic computing

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    GECCO '14
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    GECCO '14: Genetic and Evolutionary Computation Conference
    July 12 - 16, 2014
    BC, Vancouver, Canada

    Acceptance Rates

    GECCO Comp '14 Paper Acceptance Rate 180 of 544 submissions, 33%;
    Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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    • (2015)Lifelong Learning Selection Hyper-heuristics for Constraint Satisfaction ProblemsAdvances in Artificial Intelligence and Soft Computing10.1007/978-3-319-27060-9_15(190-201)Online publication date: 30-Dec-2015

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