Recasts a class of infinite-state, infinite-action Markov renewal programs with unknown parameters as one-state programs with actions corresponding to stationary policies in the original program. Under suitable conditions, an adaptive (nonstationary) optimal policy is found in the sense of maximizing long-run expected reward per unit time. 26 pp. Ref.
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