Immunology as a Metaphor for Computational ... - Napier University

Chapter 3. Immune Systems for Scheduling 523.5 SCHED1 3 IS3.5.1 Choice of IS ModelHaving established precisely those features of the biological immune system whichwe wish to incorporate into an immune-based scheduling system, returning to thepublished literature showed that there were two obvious candidates of artificial ISmodels on which a system could be based. The first of these models, proposed in[Hightower et al., 1995], was described in detail in chapter 2, and a further model dueto [Oprea and Forrest, 1998] is described below. Although both model binary universesin which bit-strings represent both antibodies (genotypically and phenotypically)and antigens, in principle, both could be extended to include more complexrepresentations.To recap, [Hightower et al., 1995] described a binary model of the immune systemwhich was used to study the effects of evolution on the genetic encoding for antibodymolecules, which showed that robust pattern recognisers can be learned with a surprisinglysmall amount of information. In this model, each individual in a population manipulatedvia a genetic algorithm represents the genetic specification for the antibodylibraries of one immune system. Bit strings were used to represent both the genotype— libraries of gene segments — and the antibody molecules of the phenotype. Furtherwork ([Perelson et al., 1996]) provided insight into how and why the natural ISevolved as it did.Oprea in [Oprea and Forrest, 1998, Oprea and Forrest, 1999] describes a simplifiedversion of the Hightower model which was used as part of a detailed study on thesources and evolutionary significance of diversity in the biological immune system.In this model, one individual’s genome consists of a single library containing a set ofcomplete antibodies — i.e. the single antibody library represented by an individual canbe viewed as exactly the antibody repertoire. It is claimed in [Oprea and Forrest, 1999]that this does not affect the generality of the model and adding more libraries wouldnot affect the results. The aim of the work was to investigate the type of antibodyrepertoire that might evolve in relation to a given pathogenic environment.We opted to extend the more general approach taken by [Hightower et al., 1995],