Man-Machine Interface Using Fuzzy Cognitive Maps

A program for the investigation of a novel man-machine interface technology employed for reliable and robust decision processes is proposed. The proposed technology is based upon the inherent causal inference and knowledge synthesis properties of the fuzzy cognitive maps which provide a nonlinear feedback dynamical system for modeling a fuzzy causal knowledge process. Furthermore, a fuzzy cognitive map allows the synthesis of various different knowledge bases from different domain experts to generate a better and more robust knowledge representation. Based on the knowledge embedded in the predefined fuzzy cognitive maps, appropriate causal inference processes can be performed to enhance the decision making processes on various information fusion systems. Investigations are proposed on the following areas: (1) methods to map the received information data into the node states of a fuzzy cognitive map, (2) algorithms to transfer the knowledge of various domain experts to the node links of a fuzzy cognitive map, and (3) causal inference rules and evolution algorithms for data discrimination and status prediction. With the results of these investigations, a prototype decision making software module will be created to demonstrate the feasibility of the concept of using fuzzy cognitive maps for reliable and robust decision processes.