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The research presented in this thesis provides
an analysis of several key issues in genetic programming.
First, selection pressure and subtree crossover success depend
on the type of fitness-based and genetic diversity in the
population. Secondly, the rates of code growth could be controlled
by adaptively controlling both fitness-based and genetic diversity.
Thirdly, the type of search genetic programming carries out can be
described using a metaphor of hill-climbing and some knowledge of
the problem domain. Finally, the inability of dissimilar
and fit individuals, and similar and equally well fit individuals,
to produce good offspring was shown.