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The range of symbolic regression instances used throughout this
thesis provided a set
of very different behaviours. From the very difficult,
the Rastrigin function, to much easier ones, the Quartic and
Binomial-3 functions, diversity measures did not capture a similar
dynamic in previous
problems that was important to search.
One reason for this is that the continuous
fitness space in Regression experiments allows genetic programming to
easily maintain high
fitness-based diversity. This can
most easily be seen in the phenotype and entropy measures in Chapter
4 that remained at much higher levels than other domains.
The Tree-String problem from Chapter 7 would appear to be most
closely related to Regression problems with its dual and often
conflicting objectives of structure and content. Applying
the results from the Tree-String experiments to the Regression problem
suggests that
much of the future populations come from diverse individuals
that may not necessarily be the most fit in the population.
That is, in the Tree-String experiments, when considering the definition
of outliers as
better-than or equivalent-to more than half the population,
the outliers contributed a considerably higher rates of survivability
than selection. The results of the Binomial-3 instance in Chapter 7
also show that outliers play an important part in the
search process.

** Next:** 3 Future Directions
** Up:** 2 Remarks and Problem
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** Contents**
S Gustafson
2004-05-20