Optimizing the structure of hierarchical mixture of experts using genetic algorithms

This study is an effort to give a practical solution in the problem of optimizing the structure of the hierarchical mixture of experts model, which is a natural extension of the associative Gaussian mixture of experts system. We present two novel methods for optimizing such structures using genetic algorithms. Special concern is taken for reducing the computational time so as to efficiently allow the structure to "grow" while it evolves with the genetic algorithm. The main contribution of the paper lies on the efficient, topologically oriented, representations of such architectures so as to be optimized through involving genetic algorithms.