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dc.contributor.authorRavindra Lal Weeraratne Koggalageen_US
dc.description.abstractThis thesis describes how existing knowledge of certain positional features of a chess game can be implemented in a parallel evaluation function using the SIMD model. Since SMID machines are very efficient in pattern matching, it is possible to examine thousands of feature patterns associated with chess positions in parallel.en_US
dc.rightsNanyang Technological Universityen_US
dc.subjectDRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition
dc.titleComplex pattern recognition and evaluation : a knowledge-based approach to computer chessen_US
dc.contributor.supervisorGoh, Wee Lengen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Engineeringen_US
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