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This thesis examines the issue of
diversity in genetic programming. Genetic programming,
an evolutionary methodology
in the fields of machine learning and artificial intelligence,
uses a population of solutions to guide search. As such,
population diversity is an important issue.
This thesis describes a series of
carefully planned and designed experiments that provide a
detailed understanding of genetic programming, diversity
and diversity related issues. An
introduction to genetic programming is presented next, followed by
the contributions and an overview of this thesis.