Figure 7.4 shows the average over 10 runs of the number of outliers, in-liers and un-fit individuals (from left to right) at each generation (increasing from left to right) in the left plot. The number of selected individuals and the number of those which produced offspring that were selected in the following generation (the survivability) are shown in heavier lines. 95% confidence bars are plotted every ten generations for the in-lier and outlier individuals. The un-fit population is the total population size minus the in-lier and outlier populations. This measure of survivability is similar to that in [Luke, 2003] where the selection of an individual represents the relative rank of that individual in the population. The measure considers the selection method being used and is a better indicator of an individual's contribution toward the search process than the change in fitness from parent to offspring.

Every generation has a number of outliers which are rarely selected,
due to their low numbers and subsequently low probability of selection.
Thus, these outliers have almost no survivability. The right plot
in Figure 7.4 of ratios of *selected over total number*
and *survived over selected*
emphasise these effects. Here the in-liers generally have a higher
ratio of selection, which is expected, and a higher survivability than
the un-fit.
The un-fit tend to have worse survivability, which emphasizes that
the in-liers produce more offspring that are able to survive and contribute
offspring in the next generation.
The survivability of the in-liers tends to lower toward the
end of the run, which is likely due to convergence, i.e.
the in-liers are unable to produce useful variations.

In this initial experiment, outlier individuals have an average pair-wise edit distance greater than 2 standard deviations from the population mean and are better than over half of the population in fitness. The number of outliers in Figure 7.4 highlights the fact that the population contains good individuals that are structurally unlike the rest of the population, are unlikely to be selected due to their few numbers, and, without more experimental results, have an intuitively lower chance of producing good offspring.

The above definition of outliers addresses the concepts of fitness and genetic
diversity, but it is not the only possibility.
For example, the fitness component in the outlier definition requires
an outlier to be better-than more than half the current population.
It may be beneficial to also consider individuals with equivalent fitness
values in this definition.
To further investigate the role of genetic diversity and survivability,
three additional experiments are performed, summarised in Table
7.2, by adjusting the fitness and dissimilarity components that
define outliers.
The following alternative definitions provide *alternative views*
of the survivability of different regions of the population. The
evolutionary process is the same for all definitions of outliers, and
as above, each alternative is considered using the averages of 10
random runs.

fitness component | difference component | ||

Fig. 7.4 | better-than | , | 2 standard deviations |

Fig. 7.6 | better-than | , | 1 standard deviations |

Fig. 7.5 | (better-than equivalent-to) | , | 2 standard deviations |

Fig. 7.7 | (better-than equivalent-to) | , | 1 standard deviations |