Abstract
Neutral networks, which occur in fitness landscapes containingneighboring points of equal fitness, have attracted much researchinterest in recent years.In a recent paper, we have shown that, in the case of the simple testfunctions, the mutation rate of a genetic algorithm is an importantfactor for improving the speed at which a population moves along aneutral network. Our results also suggested that the benefits of the variable mutationrate strategy used by the operon-GA become increasingly clear as theruggedness of the landscapes increases. In this paper, we conducted a series of computer simulations with adifficult evolutionary robotics problem showing phases of neutralevolution in order to investigate whether our previous resultsare applicable to this problem. It is found that those evolutionary dynamics are consistent with our previous results. The variable mutation rate strategy is also beneficial with thisproblem.
