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Exploiting Parallelism Inherent in AIRS, an Artificial Immune Classifier

Watkins, Andrew and Timmis, Jon (2004) Exploiting Parallelism Inherent in AIRS, an Artificial Immune Classifier. In: Nicosia, Giuseppe, ed. Artificial Immune Systems Third International Conference. Lecture Notes in Computer Science . Springer, pp. 427-438. ISBN 978-3-540-23097-7. E-ISBN 978-3-540-30220-9. (doi:10.1007/978-3-540-30220-9_34) (KAR id:14101)

Language: English
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The mammalian immune system is a highly complex, inherently parallel, distributed system. The field of Artificial Immune Systems (AIS) has developed a wide variety of algorithms inspired by the immune system, few of which appear to capitalize on the parallel nature of the system from which inspiration was taken. The work in this paper presents the first steps at realizing a parallel artificial immune system for classification. A simple parallel version of the classification algorithm Artificial Immune Recognition System (AIRS) is presented. Initial results indicate that a decrease in overall runtime can be achieved through fairly naive techniques. The need for more theoretical models of the behaviour of the algorithm is discussed.

Item Type: Book section
DOI/Identification number: 10.1007/978-3-540-30220-9_34
Uncontrolled keywords: artificial immune systems
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Mark Wheadon
Date Deposited: 24 Nov 2008 18:01 UTC
Last Modified: 16 Feb 2021 12:24 UTC
Resource URI: (The current URI for this page, for reference purposes)
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