The Challenge of Hierarchical Difficulty

Abstract

Thus far, we have examined the Bayesian optimization algorithm (BOA), empirical results of its application to several problems of bounded difficulty, and the scalability theory supporting those empirical results. It has been shown that BOA can tackle problems that are decomposable into subproblems of bounded order in a scalable manner and that it outperforms local search methods and standard genetic algorithms on difficult decomposable problems. But can BOA be extended beyond problems of bounded difficulty to solve other important classes of problems? What other classes of problems should be considered?