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Learning Recursive Functions with Object Oriented Genetic Programming

, and . Proceedings of the 9th European Conference on Genetic Programming, volume 3905 of Lecture Notes in Computer Science, page 166--177. Budapest, Hungary, Springer, (10 - 12 April 2006)

Abstract

This paper describes the evolution of recursive functions within an Object-Oriented Genetic Programming (OOGP) system. We evolved general solutions to factorial, Fibonacci, exponentiation, even-n-Parity, and nth-3. We report the computational effort required to evolve these methods and provide a comparison between crossover and mutation variation operators, and also undirected random search. We found that the evolutionary algorithms performed much better than undirected random search, and that mutation outperformed crossover on most problems.

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