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).

This page is copyrighted by AAAI. All rights reserved. Your use of this site constitutes acceptance of all of AAAI's terms and conditions and privacy policy.