Causal coding and control for Markov chains

Abstract

A Markov chain is controlled by a decision maker receiving his observations of the state via a noisy memoriless channel. That information is encoded causally. The encoder is assumed to have perfect channel feedback information. Separation results are derived and used to prove that encoding is useless for a class of symmetric channels. This paper extends the results of the authors (1983) by using methods similar to those of that paper.