Geodesic
Average cost Markov control processes with weighted norms: value iteration
Applicationes Mathematicae, Tome 23 (1996) no. 2, pp. 219-237 Cet article a éte moissonné depuis la source Institute of Mathematics Polish Academy of Sciences

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This paper shows the convergence of the value iteration (or successive approximations) algorithm for average cost (AC) Markov control processes on Borel spaces, with possibly unbounded cost, under appropriate hypotheses on weighted norms for the cost function and the transition law. It is also shown that the aforementioned convergence implies strong forms of AC-optimality and the existence of forecast horizons.
DOI : 10.4064/am-23-2-219-237
Keywords: average cost optimality equation, strong average optimality, (discrete-time) Markov control processes, long-run average cost, weighted norms

Evgueni Gordienko 1 ; Onésimo Hernández-Lerma 1

1 
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Evgueni Gordienko; Onésimo Hernández-Lerma. Average cost Markov control processes with weighted norms: value iteration. Applicationes Mathematicae, Tome 23 (1996) no. 2, pp. 219-237. doi: 10.4064/am-23-2-219-237

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