Representation and processing of domain knowledge for simulation-based training in complex dynamic systems

Abstract

Mainly because of the inability to explicitly represent declarative and procedural knowledge and operational skills in complex dynamic systems, the conventional techniques for development of intelligent tutoring systems in narrow and simple domains cannot be applied to intelligent simulation-based systems for training in complex dynamic systems. A knowledge representation language is presented that explicitly expresses the system structure, functions, and behavior. Different types of training tasks (for example, measuring, monitoring, control, and diagnostic) for quantitative modeling of continuous, discrete and discrete-event systems can be programmed in this language. On the basis of a graph interpretation of the program in knowledge representation, language task and the student's evaluation are discussed. The architecture of an environment for producing intelligent simulation-based systems for training in complex dynamic systems is described.