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dc.contributor.authorSuleman, Hussein
dc.date.accessioned2016-06-27T19:03:32Z
dc.date.available2016-06-27T19:03:32Z
dc.date.issued1997-01
dc.identifiereprint:263
dc.identifier.urihttp://hdl.handle.net/10919/71533
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_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.subjectgenetic programmingen_US
dc.subjectMathematica algorithmsen_US
dc.subjectparallel migrationen_US
dc.subjectisland-parallelismen_US
dc.subject.lccQA75
dc.titleGenetic Programming in Mathematicaen_US
dc.typeThesisen_US
dc.contributor.departmentComputer Scienceen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorUniversity of Durban-Westvilleen_US


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