A Model for the Analysis of Markovian Decision Processes with Unobservable States and Unobservable Costs.

by Jessica Steele


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Consider a finite-state finite-action Markovian decision process with unobservable costs in the sense that the total discounted cost is to be assessed at infinity. It is assumed that the initial probability distribution over the state space is known. A new Markovian decision process is then constructed having the same action space as before, but with the new state space being the set of all probability distributions over the original state space. Two sets of policies are defined and some immediate results are developed. 8 pp. Bibliog.

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