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

Chapter 5. EA Based Model — COSDM 131Number of schemas Defined Length Average Defineds d Overlap2 8 1.062 16 4.092 32 20.615 8 1.115 16 4.925 32 21.2210 8 1.0610 16 4.7610 32 21.55Table 5.3: The table shows the average defined overlap between the entire schema setfor each set of experiments performed using random non-stationary data.5.5.1 ResultsFigure 5.7 shows example outputs from experiments in which s 5, and 8¤ d 32,and 1¤ g 5. The graphs illustrate the overall trends observed in all experiments:at each antigen update following the tolerization period, there is a rapid drop in r,immediately followed by a rise in fitness during the next 50 generation period overwhich the maximum fitness achieved attains a similar level to that observed beforethe change. Higher values of r are achieved when Q g s in all cases, but when d issmall (and hence there is very little defined overlap between schemas), there is littleobservable difference as g varies.Further analysis of the results shows an approximately linear relationship betweenthe magnitude of the drop in fitness following each antigen update and the number ofschemas defining antigens that are replaced for all values of s and d tested. Figure 5.8shows representative results obtained when d 16 and 5¤ s 10. As the number ofantigens replaced increases, it is clear that the system is less likely to be able to clusterthe new data, especially as A g s. Note however, that even in the extreme case when