Artificial Immune Systems as a Novel Soft Computing Paradigm

de Castro, Leandro N. and Timmis, Jon (2003) Artificial Immune Systems as a Novel Soft Computing Paradigm. Soft Computing, 7 (8). pp. 526-544. ISSN 1432-7643. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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Artificial immune systems (AIS) can be defined as computational systems inspired by theoretical immunology, observed immune functions, principles and mechanisms in order to solve problems. Their development and application domains follow those of soft computing paradigms such as artificial neural networks (ANN), evolutionary algorithms (EA) and fuzzy systems (FS). Despite some isolated efforts, the field of AIS still lacks an adequate framework for design, interpretation and application. This paper proposes one such framework, discusses the suitability of AIS as a novel soft computing paradigm and reviews those works from the literature that integrate AIS with other approaches, focusing ANN, EA and FS. Similarities and differences between AIS and each of the other approaches are outlined. New trends on how to create hybrids of these paradigms and what could be the benefits of this hybridization are also presented.

Item Type: Article
Uncontrolled keywords: artificial immune systems, classification, supervised learning, soft computing
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Science Technology and Medical Studies > School of Computing > Applied and Interdisciplinary Informatics Group
Depositing User: Mark Wheadon
Date Deposited: 24 Nov 2008 18:00
Last Modified: 01 Jul 2014 10:26
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