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Automatic Modularization in Genetic Programming
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology.
2011 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

This master’s thesis is an investigation into automatically created functions when applying Genetic Programming to a problem. The thesis begins with a description of Genetic Programming and the different parts that is required to apply Genetic Programming to a problem. This is followed by descriptions of different methods for automatically creating functions when using Genetic Programming as a problem solving method. A new method for automatically creating functions is proposed with the name Structural Module Creation. Structural Module Creation creates new functions based on the most frequent subtrees in the population of individuals. Experiments are conducted on the even-k-parity problem to compare Structural Module Creation to Module Acquisition (another modularization method) and Genetic Programming without a modularization method. The result of the different experiments showed no improvement when using Structural Module Creation compared to Module Acquisition and Genetic Programming without a modularization method. The conclusion that can be drawn is that Structural Module Creation is not applicable to the even-k-parity problem. Appendix A contains graphs depicting the different experiments. Appendix B contains a description of the implementation of the system.

Place, publisher, year, edition, pages
2011.
Series
IT, 11 014
Identifiers
URN: urn:nbn:se:uu:diva-150822OAI: oai:DiVA.org:uu-150822DiVA: diva2:408955
Uppsok
Technology
Supervisors
Examiners
Available from: 2011-04-06 Created: 2011-04-06 Last updated: 2011-04-06Bibliographically approved

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