Continuous inference networks for autonomous systems

Abstract

The authors describe a structure for establishing the existence of fuzzy properties or patterns from a hierarchical sequence of fuzzy subproperties. The structure, referred to as a continuous inference network, consists of nodes that combine information of differing degrees of significance as well as differing degrees of existence. A discussion of characteristics of node transfer functions needed in the autonomous underwater vehicle/remotely operated vehicle (AUV/ROV) controller software and integration with neural network subsystems is included.<>