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2013 | 42 | nr 3 | 593--612
Tytuł artykułu

Optimal Stopping Model with Unknown Transition Probabilities

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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. (original abstract)
Opis fizyczny
  • Kanagawa University, Japan
  • University of Liverpool, United Kingdom
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