Geometric Optimisation using Karva for Graphical Processing Units

摘要

Population-based evolutionary algorithms continue to play an important role in artifically intelligent systems, but can not always easily use parallel computation. We have combined 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 accelerate 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 particle 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 fitness function is inordinately expensive to compute.