LEARNING CONTROL ALGORITHMS IN REAL DYNAMIC SYSTEMS.

Abstract

Learning control techniques based on decision theory and adaptive threshold logic are investigated in a real application, the control of a steam engine. The results indicate two major difficulties in the application which are discussed. It is shown that the human operator can be a good teacher if he is allowed to communicate using natural language.