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Conceptual and Practical Aspects of the aiNet Family of Algorithms
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Author(s): Fabrício O. de França (University of Campinas, Unicamp, Brazil), Guilherme P. Coelho (University of Campinas, Unicamp, Brazil), Pablo A.D. Castro (University of Campinas, Unicamp, Brazil)and Fernando J. Von Zuben (University of Campinas, Unicamp, Brazil)
Copyright: 2012
Pages: 38
Source title:
Nature-Inspired Computing Design, Development, and Applications
Source Author(s)/Editor(s): Leandro Nunes de Castro (Mackenzie University, Brazil)
DOI: 10.4018/978-1-4666-1574-8.ch001
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Abstract
In this paper, a review of the conceptual and practical aspects of the aiNet (Artificial Immune Network) family of algorithms will be provided. This family of algorithms started with the aiNet algorithm, proposed in 2002 for data clustering and, since then, several variations have been developed for data clustering, biclustering and optimization in general. Although the algorithms will be positioned with respect to other pertinent approaches from the literature, the emphasis of this paper will be on the formalization and critical analysis of the set of contributions produced along almost one decade of research in this specific theme, together with the provision of insights for further extensions.
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