Fuzzy logic and fuzzy systems: recent developments and future directions

Abstract

Over the last decade or so, several parallel advances have been made in the two distinct disciplines: fuzzy logic and neural networks. As the names imply, the theory of fuzzy logic provides a mathematical framework for the emulation of certain perceptual and linguistic attributes associated with human cognition, whereas the science of neural networks provides new computing morphologies with learning and adaptive capabilities. A marriage between these two distinct disciplines has the potential of producing robotic machines with some sort of cognitive abilities. We briefly examine these two fields: fuzzy logic and neural networks, and explore the possibilities of their integration in the development of cognitive robotic systems.