Genetic Fuzzy Systems: Status, Critical Considerations and Future Directions

Fuzzy Systems have shown their utility for solving a wide range of problems in different application domains. The use of Genetic Algorithms for designing Fuzzy Systems allows us to introduce the learning and adaptation capabilities. This topic has attracted considerable attention in the Computation Intelligence community. This short paper briefly reviews the classical models and the most recent trends for Genetic Fuzzy Systems. We pay special attention to a short discussion on some critical considerations of recent developments and to the suggestion of potential research future directions.