Adaptive control of discrete time Markov processes by the method of large deviations

Abstract

Adaptive control strategies for discrete time Markov processes are constructed using the uniform, large deviations of empirical distributions. The adaptive procedure is based on the construction of a finite set of continuous nearly optimal control functions, and implies that in a finite time interval a control function exists that is almost optimal with probability close to 1.