Learning Sorting Networks By Grammars

Thomas E. Kammeyer, Richard K. Belew

We use a genetic algorithm(GA) to search for CMPX-nets which are SNets or MNets. The GA repeatedly samples the space of potential solutions in a series of generations, each using the relative fitness of the previous generation’s samples to apportion more samples in promising regions. Mutation and especially cross-over operators are applied to generate similar but novel new sample points; this process is iterated until some stopping criterion is achieved. Hillis has had encouraging success using a GA to evolve sorting networks( Hillis 1991).


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