A Counterexample on Sample-Path Optimality in Stable Markov Decision Chains with the Average Reward Criterion

Rolando Cavazos-Cadena (), Raúl Montes- de-Oca () and Karel Sladký ()
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Rolando Cavazos-Cadena: Universidad Autónoma Agraria Antonio Narro
Raúl Montes- de-Oca: Universidad Autónoma Metropolitana
Karel Sladký: Institute of Information Theory and Automation

Journal of Optimization Theory and Applications, 2014, vol. 163, issue 2, No 17, 674-684

Abstract: Abstract This note deals with Markov decision chains evolving on a denumerable state space. Under standard continuity-compactness requirements, an explicit example is provided to show that, with respect to a strong sample-path average reward criterion, the Lyapunov function condition does not ensure the existence of an optimal stationary policy.

Keywords: Strong sample-path optimality; Lyapunov function condition; Stationary policy; Expected average reward criterion (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10957-013-0474-6

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