LIMITED RANDOMIZATION FOR MARKOV DECISION PROCESSES WITH MULTIPLE CONSTRAINTS.

Keith Ross

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    We consider the Markov decision problem of finding a policy to maximize the long-run average reward subject to K long-run average cost constraints. We show that there exists an optimal policy with a degree of randomization less than or equal to K. Consequently, it is never necessary to randomize in more than K states. An algorithm employing linear programming is shown to produce the optimal policy with the limited-randomization property.

    Original languageEnglish (US)
    Title of host publicationUnknown Host Publication Title
    PublisherPrinceton Univ
    Pages649-651
    Number of pages3
    StatePublished - 1986

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    Linear programming
    Costs

    ASJC Scopus subject areas

    • Engineering(all)

    Cite this

    Ross, K. (1986). LIMITED RANDOMIZATION FOR MARKOV DECISION PROCESSES WITH MULTIPLE CONSTRAINTS. In Unknown Host Publication Title (pp. 649-651). Princeton Univ.

    LIMITED RANDOMIZATION FOR MARKOV DECISION PROCESSES WITH MULTIPLE CONSTRAINTS. / Ross, Keith.

    Unknown Host Publication Title. Princeton Univ, 1986. p. 649-651.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Ross, K 1986, LIMITED RANDOMIZATION FOR MARKOV DECISION PROCESSES WITH MULTIPLE CONSTRAINTS. in Unknown Host Publication Title. Princeton Univ, pp. 649-651.
    Ross K. LIMITED RANDOMIZATION FOR MARKOV DECISION PROCESSES WITH MULTIPLE CONSTRAINTS. In Unknown Host Publication Title. Princeton Univ. 1986. p. 649-651
    Ross, Keith. / LIMITED RANDOMIZATION FOR MARKOV DECISION PROCESSES WITH MULTIPLE CONSTRAINTS. Unknown Host Publication Title. Princeton Univ, 1986. pp. 649-651
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