"Sustaining the diversity of evolving populations is a fundamental issue in genetic programming. We describe a novel measure of structural diversity for tree-based genetic programming, and we demonstrate its utility compared to other diversity techniques. We demonstrate our technique on the real-world application of tuberculosis screening from X-ray images. We then introduce a new paradigm of genetic programming that involves simultaneously maintaining structural and behavioral diversity in order to further improve the efficiency of genetic programming. Our results show that simultaneously promoting structural and behavioral diversity improves genetic programming by leveraging the benefits of both aspects of diversity while overcoming the shortcomings of either technique in isolation. The hybridization increases the behavioral diversity of our structural diversity technique, and increases the structural diversity of the behavioral diversity techniques. This increased diversity leads to performance gains compared to either technique in isolation. We found that in many cases, our structural diversity technique provides significant performance improvement compared to other state-of-the-art techniques. Our results from the experiments comparing the hybrid techniques indicate that the largest performance gain was typically attributed to our structural diversity technique. The incorporation of the behavioral diversity techniques provide additional improvement in many cases."--Page ii.
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