ISBN: 9786131750595 - markov decision process: andrey markov, partially observable markov decision process, markov property, optimal control theory, tuple, stochastic, discrete time (3 risultati)

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  • Lingua: Inglese

    Editore: Omniscriptum Mär 2026, 2026

    6131750599 / 9786131750595

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    EUR 116,00

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    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 72 pp. Englisch.

  • Lingua: Inglese

    Editore: Omniscriptum, 2010

    6131750599 / 9786131750595

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    EUR 123,17

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    Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Please note that the content of this book primarily consists of articlesavailable from Wikipedia or other free sources online. Markov decisionprocesses (MDPs), named after Andrey Markov, provide a mathematicalframework for modeling decision-making in situations where outcomes arepartly random and partly under the control of a decision maker. MDPs areuseful for studying a wide range of optimization problems solved viadynamic programming and reinforcement learning. MDPs were known at leastas early as the 1950s (cf. Bellman 1957). Much research in the area wasspawned due to Ronald A. Howard's book, Dynamic Programming and MarkovProcesses, in 1960. Today they are used in a variety of areas, includingrobotics, automated control, economics and manufacturing.…

  • Lingua: Inglese

    Editore: Omniscriptum Mär 2026, 2026

    6131750599 / 9786131750595

    • Brossura
    • Print on Demand

    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Condizione: Nuovo

    EUR 116,00

    EUR 60,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 1 disponibile

    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Please note that the content of this book primarily consists of articlesavailable from Wikipedia or other free sources online. Markov decisionprocesses (MDPs), named after Andrey Markov, provide a mathematicalframework for modeling decision-making in situations where outcomes arepartly random and partly under the control of a decision maker. MDPs areuseful for studying a wide range of optimization problems solved viadynamic programming and reinforcement learning. MDPs were known at leastas early as the 1950s (cf. Bellman 1957). Much research in the area wasspawned due to Ronald A. Howard's book, Dynamic Programming and MarkovProcesses, in 1960. Today they are used in a variety of areas, includingrobotics, automated control, economics and manufacturing.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 72 pp. Englisch.…