• DocumentCode
    2409071
  • Title

    Adaptive control of i.i.d. processes and Markov chains on a compact control set

  • Author

    Agrawal, Rajeev

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA
  • fYear
    1992
  • fDate
    1992
  • Firstpage
    2752
  • Abstract
    The author considers the multiarmed bandit problem and the adaptive control of Markov chains with continuous arms that are chosen from a compact subset of IRd. A learning scheme based on a kernel estimator is devised. Using this learning scheme, the author constructs a class of certainty equivalence control with forcing schemes and derives asymptotic upper bounds on their learning loss
  • Keywords
    Markov processes; adaptive control; estimation theory; game theory; learning systems; Markov chains; adaptive control; asymptotic upper bounds; certainty equivalence control; compact control set; forcing schemes; i.i.d. processes; kernel estimator; learning loss; learning scheme; multiarmed bandit problem; Adaptive control; Arm; Context modeling; Control systems; Kernel; Process control; Stochastic processes; Stochastic systems; Upper bound;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1992., Proceedings of the 31st IEEE Conference on
  • Conference_Location
    Tucson, AZ
  • Print_ISBN
    0-7803-0872-7
  • Type

    conf

  • DOI
    10.1109/CDC.1992.371317
  • Filename
    371317
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2409071