On Maximizing the Average Time at a Goal

S. Demko, Georgia Institute of Technology - Main Campus
Theodore P. Hill, Georgia Institute of Technology - Main Campus

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Copyright © 1984 Elsevier. The definitive version is available at http://dx.doi.org/10.1016/0304-4149(84)90010-3 .

NOTE: At the time of publication, the author Theodore P. Hill was not yet affiliated with Cal Poly.

Abstract

In a decision process (gambling or dynamic programming problem) with finite state space and arbitrary decision sets (gambles or actions), there is always available a Markov strategy which uniformly (nearly) maximizes the average time spent at a goal. If the decision sets are closed, there is even a stationary strategy with the same property.Examples are given to show that approximations by discounted or finite horizon payoffs are not useful for the general average reward problem.