Extrema selection: accelerated evolution on neutral networks

A new modification to the genetic algorithm is presented which is specifically designed to increase the rate of evolution on fitness functions with high degrees of neutrality (mutations that do not change the individual´s fitness). Instead of allowing random genetic drift to occur when most of the population has reached the same fitness, the “reproduction fitness” of individuals is set to their distance from the population centroid. This has the theoretical effect of spreading the population quickly across the neutral network, and thus finding regions of higher fitness more quickly than it mould otherwise. A series of experiments is described which shows a significant improvement in using this method on the NKp family of fitness functions, and show that this improvement is correlated with the degree of neutrality