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dc.contributor.authorWalker, Matthew Garry William
dc.date.accessioned2009-04-17T02:17:23Z
dc.date.availableNO_RESTRICTIONen_US
dc.date.available2009-04-17T02:17:23Z
dc.date.issued2007
dc.identifier.urihttp://hdl.handle.net/10179/738
dc.description.abstractThis thesis is divided into two parts. The first part considers and develops some of the statistics used in genetic programming (GP) while the second uses those statistics to study and develop a form of incremental evolution and an early termination heuristic for GP. The first part looks in detail at success proportion, Koza's minimum computational effort, and a measure we rename "success effort". We describe and develop methods to produce confidence intervals for these measures as well as confidence intervals for the difference and ratio of these measures. The second part studies Jackson's fitness-based incremental evolution. If the number of fitness evaluations are considered (rather than the number of generations) then we find some potential benefit through reduction in the effort required to find a solution. We then automate the incremental evolution method and show a statistically significant improvement compared to GP with automatically defined functions (ADFs). The success effort measure is shown to have the critical advantage over Koza's measure as it has the ability to include a decreasing cost of failure. We capitalise on this advantage by demonstrating an early termination heuristic that again offers a statistically significant advantage.en_US
dc.language.isoenen_US
dc.publisherMassey Universityen_US
dc.rightsThe Authoren_US
dc.subjectIncremental evolutionen_US
dc.subjectGenetic programmingen_US
dc.subjectPerformance measuresen_US
dc.subject.otherFields of Research::280000 Information, Computing and Communication Sciencesen_US
dc.titleDeveloping and evaluating incremental evolution using high quality performance measures for genetic programming : a thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosphy in Computer Science at Massey University, Albany, Auckland, New Zealanden_US
dc.typeThesisen_US
thesis.degree.disciplineComputer Scienceen_US
thesis.degree.grantorMassey Universityen_US
thesis.degree.levelDoctoralen_US
thesis.degree.levelDoctoralen
thesis.degree.nameDoctor of Philosophy (Ph.D.)en_US


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