Geometric Optimisation using Karva for Graphical Processing Units
Alwyn V. Husselmann, Ken A. Hawick · 2013
Population-based evolutionary algorithms continue to play an important role in artifically intelligent systems, but can not always easily use parallel computation. We have com- bined a geometric (any-space) particle swarm optimisation algorithm with use of Ferreira's Karva language of gene expression programming to produce a hybrid that can ac- celerate the genetic operators and which can rapidly attain a good solution. We show how Graphical Processing Units (GPUs) can be exploited for this. While the geometric par- ticle swarm optimiser is not markedly faster that genetic programming, we show it does attain good solutions faster, which is important for the problems discussed when the fit- ness function is inordinately expensive to compute.