A basic formula for performance gradient estimation of semi-Markov decision processes
AbstractThis paper presents a basic formula for performance gradient estimation of semi-Markov decision processes (SMDPs) under average-reward criterion. This formula directly follows from a sensitivity equation in perturbation analysis. With this formula, we develop three sample-path-based gradient estimation algorithms by using a single sample path. These algorithms naturally extend many gradient estimation algorithms for discrete-time Markov systems to continuous time semi-Markov models. In particular, they require less storage than the algorithm in the literature.
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Bibliographic InfoArticle provided by Elsevier in its journal European Journal of Operational Research.
Volume (Year): 224 (2013)
Issue (Month): 2 ()
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Web page: http://www.elsevier.com/locate/eor
Markov processes; Semi-Markov decision processes; Sample-path-based gradient estimation; Perturbation analysis;
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- Singh, Sumeetpal S. & Tadic, Vladislav B. & Doucet, Arnaud, 2007. "A policy gradient method for semi-Markov decision processes with application to call admission control," European Journal of Operational Research, Elsevier, vol. 178(3), pages 808-818, May.
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