On maximizing the average time at a goal

S. Demko and T. P. Hill

Stochastic Processes and their Applications, 1984, vol. 17, issue 2, 349-357

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.

Keywords: gambling; theory; goal; problems; dynamic; programming; stationary; strategy; Markov; strategy; average; reward; criterion (search for similar items in EconPapers)
Date: 1984
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