System Optimization via Learning and Adaptation

ABSTRACT This paper presents an approach to the design of adaptive and learning systems for achieving optimal control. The design procedure makes use of decision theory and dynamic programming. The system up-dates the knowledge of the probability density function on the basis of the observed information pattern, The fresh information which is learned during each stage is used in performing the optimization process.