ABSTRACT
The chapter presents various behavioral models of cognition, built with fuzzy neural nets for applications in man-machine interface, automated coordination and learning control systems. It starts with a simple model of a fuzzy neural net that mimics the activities of “long term memory” of the biological cognitive system. The model has the potential of both reasoning and automated learning on a common structure. The model is then extended with Petri nets to represent and reason with more complex knowledge of the real world. A second model presented in this chapter is designed for application in a learning control system. It emulates the task of the motor controller for the limb movements in the biological cognitive system. An example of the automated eye-hand coordination problem for robots has also been presented here with timed Petri net models. The chapter ends with a discussion of the possible application of the proposed models in a composite robotic system.
