Hierarchical Genetic Fuzzy Systems: Accuracy, Interpretability and Design Autonomy

This chapter addresses hierarchical evolutionary rule-based fuzzy modeling, focusing on accuracy, interpretability and design autonomy issues. Special attention is given to interpretability in terms of visibility, simplicity, compactness, and consistency. As a consequence, fuzzy modeling is viewed as a decision making problem where accuracy, interpretability and autonomy are goals. The approach assumes that goals can be handled via corresponding single-objective ε-constrained decision making problems whose solution is produced by a hierarchical evolutionary process based on genetic algorithms, namely, a hierarchical genetic fuzzy system. In addition to performance improvement and interpretability constraints fulfillment, the hierarchical approach allows automatic tuning of a number of critical parameters and increases autonomy by minimizing user intervention. The fitting, generalization, and interpretation characteristics of the resulting fuzzy models are discussed using function approximation and classification problems.