LP based upper and lower bounds for Cesàro and Abel limits of the optimal values in problems of control of stochastic discrete time systems

Konstantin Avrachenkov, Vladimir Gaitsgory, Lucas Gamertsfelder*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    2 Citations (Scopus)

    Abstract

    In this paper, we study asymptotic properties of problems of control of stochastic discrete time systems (also known as Markov decision processes) with time averaging and time discounting optimality criteria, and we establish that the Cesàro and Abel limits of the optimal values in such problems can be evaluated with the help of a certain infinite-dimensional linear programming problem and its dual.

    Original languageEnglish
    Article number126121
    Pages (from-to)1-54
    Number of pages54
    JournalJournal of Mathematical Analysis and Applications
    Volume512
    Issue number1
    DOIs
    Publication statusPublished - 1 Aug 2022

    Keywords

    • Stochastic optimal control
    • Markov decision processes (MDPs)
    • Linear programming
    • Optimality conditions
    • Dynamic programming
    • Discrete time

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