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May, 1973 Markov Decision Processes with a New Optimality Criterion: Discrete Time
Stratton C. Jaquette
Ann. Statist. 1(3): 496-505 (May, 1973). DOI: 10.1214/aos/1176342415

Abstract

Standard finite state and action discrete time Markov decision processes with discounting are studied using a new optimality criterion called moment optimality. A policy is moment optimal if it lexicographically maximizes the sequence of signed moments of total discounted return with a positive (negative) sign if the moment is odd (even). This criterion is equivalent to being a little risk adverse. It is shown that a stationary policy is moment optimal by examining the negative of the Laplace transform of the total return random variable. An algorithm to construct all stationary moment optimal policies is developed. The algorithm is shown to be finite.

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Stratton C. Jaquette. "Markov Decision Processes with a New Optimality Criterion: Discrete Time." Ann. Statist. 1 (3) 496 - 505, May, 1973. https://doi.org/10.1214/aos/1176342415

Information

Published: May, 1973
First available in Project Euclid: 12 April 2007

zbMATH: 0259.90054
MathSciNet: MR378839
Digital Object Identifier: 10.1214/aos/1176342415

Rights: Copyright © 1973 Institute of Mathematical Statistics

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Vol.1 • No. 3 • May, 1973
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