Grammar Transformations in an EDA for Genetic Programming
Peter A. N. Bosman, Edwin D. de Jong · 2004
Abstract. In this paper we present a new Estimation–of–Distribution Algorithm (EDA) for Genetic Programming (GP). We propose a proba-bility distribution for the space of trees, based on a grammar. To intro-duce dependencies into the distribution, grammar transformations are performed that facilitate the description of specific subfunctions. We present some results from experiments on two benchmark problems and show some of the subfunctions that were introduced during optimization as a result of the transformations that were applied. 1