Mutation as a diversity enhancing mechanism in genetic programming
David Jackson · 2011
In various evolutionary computing algorithms, mutation operators are employed as a means of preserving diversity of populations. In genetic programming (GP), by contrast, mutation tends to be viewed as offering little benefit, to the extent that it is often not implemented in GP systems. We investigate the role of mutation in GP, and attempt to answer questions regarding its effectiveness as a means for enhancing diversity, and the consequent effects of any such diversity promotion on the solution finding performance of the algorithm. We find that mutation can be beneficial for GP, but subject to the proviso that it be tailored to enhance particular forms of diversity.