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Optimal stopping model with unknown transition probabilities

Horiguchi M., Piunovskiy A. B.

Control and Cybernetics

2013

Vol. 42, no. 3

593--612

This article concerns the optimal stopping problem for a discrete-time Markov chain with observable states, but with unknown transition probabilities. A stopping policy is graded via the expected total-cost criterion resulting from the non-negative running and terminal costs. The Dynamic Programming method, combined with the Bayesian approach, is developed. A series of explicitly solved meaningful examples illustrates all the theoretical issues.