On Finding the Maximal Gain for Markov Decision Processes

Abstract

The method of successive approximations for solving problems on single-chain Markovian decision processes has been investigated by White and Schweitzer. This paper shows that White's scheme not only converges, but also can be modified so that monotonic upper and lower bounds on the maximal gain can be obtained.