Mutational Robustness and Structural Complexity in Grammatical Evolution
Michael O’Neill, Anthony Brabazon · 2019
A recent study in Artificial Life found that the need for mutational robustness can give rise to simpler structures in an evolving population. This begs the question, do we observe a similar phenomenon in Genetic Programming? Genetic Programming requires the search of structural space of solutions, usually requiring code growth to find fitter solutions. Typically Genetic Programming algorithms then suffer from code bloat, which is code growth in the absence of fitness gains. In this study we ask a simple question. Would the necessity for mutational robustness under selection pressure drive the evolution of less complex solution structures in Genetic Programming, with the potential to counteract code bloat?