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  • 1
    Electronic Resource
    Electronic Resource
    A mathematical programming approach to a problem in variance penalised Markov decision processes (1994)
    Springer
    OR spectrum 15 (1994), S. 225-230 
    Details
    ISSN: 1436-6304
    Keywords: Markov decision processes ; ɛ-optimal ; variance ; Markov'sche Entscheidungsprozesse ; ɛ-Optimalität ; Gewinnvarianz
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Description / Table of Contents: Zusammenfassung In dieser Arbeit geben wir drei Algorithmen zur Lösung eines stochastischen dynamischen Problems an. Dabei wird ein optimaler Ausgleich zwischen erwartetem Gewinn und Gewinnvarianz pro Zeiteinheit gesucht. Die Algorithmen liefern für beliebigesɛ〉0 jeweilsɛ-optimale Lösungen.
    Notes: Abstract In this paper we present three algorithms for solving a problem in which it is required to get an optimal compromise between the average expected reward per unit time and the variance of the reward per unit time. The algorithms lead to anɛ-optimal solution, whereɛ〉0 is arbitrary.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01719453
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  • 2
    Electronic Resource
    Electronic Resource
    Mean, variance, and probabilistic criteria in finite Markov decision processes: A review (1988)
    Springer
    Journal of optimization theory and applications 56 (1988), S. 1-29 
    Details
    ISSN: 1573-2878
    Keywords: Markov decision processes ; infinite horizon ; finite horizon ; mean ; variance ; probabilistic criteria
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract This paper is a survey of papers which make use of nonstandard Markov decision process criteria (i.e., those which do not seek simply to optimize expected returns per unit time or expected discounted return). It covers infinite-horizon nondiscounted formulations, infinite-horizon discounted formulations, and finite-horizon formulations. For problem formulations in terms solely of the probabilities of being in each state and taking each action, policy equivalence results are given which allow policies to be restricted to the class of Markov policies or to the randomizations of deterministic Markov policies. For problems which cannot be stated in such terms, in terms of the primitive state setI, formulations involving a redefinition of the states are examined.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00938524
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    Paper (German National Licenses)
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