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Identification of Optimal Policies in Markov Decision Processes

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    SYSNO ASEP0346161
    Document TypeJ - Journal Article
    R&D Document TypeJournal Article
    Subsidiary JČlánek ve WOS
    TitleIdentification of Optimal Policies in Markov Decision Processes
    Author(s) Sladký, Karel (UTIA-B) RID
    Source TitleKybernetika. - : Ústav teorie informace a automatizace AV ČR, v. v. i. - ISSN 0023-5954
    46 2010, č. 3 (2010), s. 558-570
    Number of pages13 s.
    ActionInternational Conference on Mathematical Methods in Economy and Industry
    Event date15.06.2009-18.06.2009
    VEvent locationČeské Budějovice
    CountryCZ - Czech Republic
    Event typeCST
    Languageeng - English
    CountryCZ - Czech Republic
    Keywordsfinite state Markov decision processes ; discounted and average costs ; elimination of suboptimal policies
    Subject RIVBB - Applied Statistics, Operational Research
    R&D ProjectsGA402/08/0107 GA ČR - Czech Science Foundation (CSF)
    GA402/07/1113 GA ČR - Czech Science Foundation (CSF)
    CEZAV0Z10750506 - UTIA-B (2005-2011)
    UT WOS000280425000019
    AnnotationIn this note we focus attention on identifying optimal policies and on elimination suboptimal policies minimizing optimality criteria in discrete-time Markov decision processes with finite state space and compact action set. We present unified approach to value iteration algorithms that enables to generate lower and upper bounds on optimal values, as well as on the current policy. Using the modified value iterations it is possible to eliminate suboptimal actions and to identify an optimal policy or nearly optimal policies in a finite number of steps without knowing precise values of the performance function.
    WorkplaceInstitute of Information Theory and Automation
    ContactMarkéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
    Year of Publishing2011
Number of the records: 1  

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