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Approximation and adaptive control of Markov processes: Average reward criterion. (English) Zbl 0633.90091

Several procedures to approximate the optimal value of average-reward controlled Markov processes with Borel state and control spaces are introduced. The procedures are then used to obtain (i) optimal policies, and (ii) optimal adaptive policies for control processes depending on unknown parameters. The latter include the well known “method of substituting the estimates into optimal stationary controls”. The approximation procedures are based on a nonstationary version of the value-iteration scheme.

MSC:

90C40 Markov and semi-Markov decision processes
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References:

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