Abstract

This paper describes an immune system model based on binary strings. The purpose of the model is to study the pattern-recognition processes and learning that take place at both the individual and species levels in the immune system. The genetic algorithm (GA) is a central component of the model. The paper reports simulation experiments on two pattern-recognition problems that are relevant to natural immune systems. Finally, it reviews the relation between the model and explicit fitness-sharing techniques for genetic algorithms, showing that the immune system model implements a form of implicit fitness sharing.

Keywords

Computer scienceArtificial immune systemComponent (thermodynamics)Genetic algorithmImmune recognitionArtificial intelligenceRelation (database)Immune systemMachine learningBinary numberAlgorithmPattern recognition (psychology)Data miningMathematicsBiology

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Publication Info

Year
1993
Type
article
Volume
1
Issue
3
Pages
191-211
Citations
259
Access
Closed

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Stephanie Forrest, Brenda Javornik, Robert E. Smith et al. (1993). Using Genetic Algorithms to Explore Pattern Recognition in the Immune System. Evolutionary Computation , 1 (3) , 191-211. https://doi.org/10.1162/evco.1993.1.3.191

Identifiers

DOI
10.1162/evco.1993.1.3.191