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Representation in the (Artificial) Immune System.

McEwan, Chris and Hart, Emma (2009) Representation in the (Artificial) Immune System. J Mathematical Modelling and Algorithms, 8 (2). pp. 125-149. ISSN 1570-1166

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Abstract/Description

Much of contemporary research in Artificial Immune Systems (AIS) has partitioned into either algorithmic machine learning and optimisation, or, modelling biologically plausible dynamical systems, with little overlap between. We propose that this dichotomy is somewhat to blame for the lack of significant advancement of the field in either direction and demonstrate how a simplistic interpretation of Perelson’s shape-space formalism may have largely contributed to this dichotomy. In this paper, we motivate and derive an alternative representational abstraction. To do so we consider the validity of shape-space from both the biological and machine learning perspectives. We then take steps towards formally integrating these perspectives into a coherent computational model of notions such as life-long learning, degeneracy, constructive representations and contextual recognition—rhetoric that has long inspired work in AIS, while remaining largely devoid of operational definition.

Item Type: Article
Print ISSN: 1570-1166
Electronic ISSN: 1572-9214
Uncontrolled Keywords: Artificial immune system;representation; shape-space - learning ;
University Divisions/Research Centres: Faculty of Engineering, Computing and Creative Industries > School of Computing
Dewey Decimal Subjects: 000 Computer science, information & general works > 000 Computer science, knowledge & systems > 003 Systems
000 Computer science, information & general works > 000 Computer science, knowledge & systems > 006 Special Computer Methods > 006.3 Artificial intelligence
600 Technology > 620 Engineering > 621 Electronic & mechanical engineering > 621.3 Electrical & electronic engineering > 621.38 Electronics & Communications engineering > 621.389 Computer engineering
Library of Congress Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Item ID: 3478
Depositing User: Computing Research
Date Deposited: 29 Jan 2010 11:57
Last Modified: 05 Mar 2010 12:54
URI: http://researchrepository.napier.ac.uk/id/eprint/3478

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