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Artificial Immunology for Collective Adaptive Systems Design and Implementation

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Published:06 June 2016Publication History
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Abstract

Distributed autonomous systems consisting of large numbers of components with no central control point need to be able to dynamically adapt their control mechanisms to deal with an unpredictable and changing environment. Existing frameworks for engineering self-adaptive systems fail to account for the need to incorporate self-expression—that is, the capability of a system to dynamically adapt its coordination pattern during runtime. Although the benefits of incorporating self-expression are well known, currently there is no principled means of enabling this during system design. We propose a conceptual framework for principled design of systems that exhibit self-expression, based on inspiration from the natural immune system. The framework is described as a set of design principles and customizable algorithms and then is instantiated in three case studies, including two from robotics and one from artificial chemistry. We show that it enables self-expression in each case, resulting in systems that are able to adapt their choice of coordination pattern during runtime to optimize functional and nonfunctional goals, as well as to discover novel patterns and architectures.

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      • Published in

        cover image ACM Transactions on Autonomous and Adaptive Systems
        ACM Transactions on Autonomous and Adaptive Systems  Volume 11, Issue 2
        Special Section on Best Papers from SASO 2014 and Regular Articles
        July 2016
        267 pages
        ISSN:1556-4665
        EISSN:1556-4703
        DOI:10.1145/2952298
        Issue’s Table of Contents

        Copyright © 2016 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 6 June 2016
        • Revised: 1 February 2016
        • Accepted: 1 February 2016
        • Received: 1 February 2015
        Published in taas Volume 11, Issue 2

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