Skip to content
University of Maryland LibrariesDigital Repository at the University of Maryland
    • Войти
    Просмотр элемента 
    •   Главная
    • A. James Clark School of Engineering
    • Institute for Systems Research Technical Reports
    • Просмотр элемента
    •   Главная
    • A. James Clark School of Engineering
    • Institute for Systems Research Technical Reports
    • Просмотр элемента
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Risk-Sensitive Optimal Control of Hidden Markov Models: A Case Study

    Thumbnail
    Открыть
    TR_94-71.pdf (185.3Kb)
    No. of downloads: 526

    Дата
    1994
    Автор
    Fernandez-Gaucherand, Emmanuel
    Marcus, Steven I.
    Metadata
    Показать полную информацию
    Аннотации
    We consider a risk-sensitive optimal control problem for hidden Markov models (HMM). Building upon recent results by Baras, James and Elliott, we investigate the structure of risk-sensitive controllers for HMM, via an examination of a popular benchmark problem. We obtain new results on the structure of the risk- sensitive controller by first proving concavity and piecewise linearity of the value function. Furthermore, we compare the structure of risk-sensitive and risk-neutral controllers.
    URI
    http://hdl.handle.net/1903/5544
    Collections
    • Institute for Systems Research Technical Reports

    DRUM is brought to you by the University of Maryland Libraries
    University of Maryland, College Park, MD 20742-7011 (301)314-1328.
    Please send us your comments.
    Web Accessibility
     

     

    Просмотр

    Весь DSpaceСообщества и коллекцииДата публикацииАвторыНазванияТематикаЭта коллекцияДата публикацииАвторыНазванияТематика

    Моя учетная запись

    ВойтиРегистрация
    Pages
    About DRUMAbout Download Statistics

    DRUM is brought to you by the University of Maryland Libraries
    University of Maryland, College Park, MD 20742-7011 (301)314-1328.
    Please send us your comments.
    Web Accessibility