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Artificial immune systems

Greensmith, Julie; Whitbrook, Amanda; Aickelin, Uwe

Authors

Julie Greensmith jqg@cs.nott.ac.uk

Amanda Whitbrook amw@cs.nott.ac.uk

Uwe Aickelin uwe.aickelin@nottingham.ac.uk



Contributors

Michel Gendreau
Editor

Jean-Yves Potvin
Editor

Abstract

The human immune system has numerous properties that make it ripe for exploitation in the computational domain, such as robustness and fault tolerance, and many different algorithms, collectively termed Artificial Immune Systems
(AIS), have been inspired by it. Two generations of AIS are currently in use, with the first generation relying on simplified immune models and the second generation utilising interdisciplinary collaboration to develop a deeper understanding of the immune system and hence produce more complex models. Both generations of algorithms have been successfully applied to a variety of problems, including anomaly detection, pattern recognition, optimisation and robotics. In this chapter an overview of AIS is presented, its evolution is discussed, and it is shown that the diversification of the field is linked to the diversity of the immune system itself, leading to a number of algorithms as opposed to one archetypal system. Two case studies are also presented to help provide insight into the mechanisms of AIS; these are the idiotypic network approach and the Dendritic Cell Algorithm.

Book Type Book Chapter
Publication Date Jan 1, 2010
Peer Reviewed Peer Reviewed
Volume 2nd ed
Issue 146
Series Title International series in operations research & management science
Book Title Handbook of metaheuristics
ISBN 9781441916631
APA6 Citation Greensmith, J., Whitbrook, A., & Aickelin, U. (2010). Artificial immune systems. In M. Gendreau, & J. Potvin (Eds.), Handbook of metaheuristicsSpringer
Publisher URL http://www.springer.com/business+%26+management/operations+research/book/978-1-4419-1663-1
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf
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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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