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Genetic Programming in Mathematica

dc.contributor.authorSuleman, Husseinen
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2016-06-27T19:03:32Zen
dc.date.available2016-06-27T19:03:32Zen
dc.date.issued1997-01en
dc.description.abstractGP has traditionally been implemented in LISP but there is a slow migration towards faster languages like C++. Any implementation language is dictated not only by the speed of the platform but also by the desirability of such an implementation. With a large number of scientists migrating to scientifically-biased programming languages like Mathematica, such provides an ideal testbed for GP.In this study it was attempted to implement GP on a Mathematica platform, exploiting the advantages of Mathematica's unique capabilities. Wherever possible, optimizations have been applied to drive the GP algorithm towards realistic goals. At an early stage it was noted that the standard GP algorithm could be significantly speeded up by parallelisation and the distribution of processing. This was incorporated into the algorithm, using known techniques and Mathematica-specific knowledge.en
dc.format.mimetypeapplication/pdfen
dc.identifiereprint:263en
dc.identifier.urihttp://hdl.handle.net/10919/71533en
dc.language.isoenen
dc.publisherUniversity of Durban-Westvilleen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectgenetic programmingen
dc.subjectMathematica algorithmsen
dc.subjectparallel migrationen
dc.subjectisland-parallelismen
dc.subject.lccQA75en
dc.titleGenetic Programming in Mathematicaen
dc.typeThesisen
thesis.degree.grantorUniversity of Durban-Westvilleen
thesis.degree.levelmastersen

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