Comparison of Policy Functions from the Optimal Learning and Adaptive Control Frameworks

D.A. Kendrick, H.M. Amman

    Research output: Working paperAcademic

    Abstract

    In this paper we turn our attention to comparing the policy function obtained by
    Beck and Wieland (2002) to the one obtained with adaptive control methods. It
    is an integral part of the optimal learning method used by Beck and Wieland to
    obtain a policy function that provides the optimal control as a feedback function
    of the state of the system. However, computing this function is not necessary
    when doing Monte Carlo experiments with adaptive control methods. Therefore, we
    have modified our software in order to obtain the policy function for comparison to
    the BW results.
    Original languageEnglish
    Place of PublicationUtrecht
    PublisherUU USE Tjalling C. Koopmans Research Institute
    Number of pages19
    Publication statusPublished - Aug 2008

    Publication series

    NameDiscussion Paper Series / Tjalling C. Koopmans Research Institute
    No.19
    Volume08
    ISSN (Electronic)2666-8238

    Keywords

    • Active learning
    • dual control
    • optimal experimentation
    • stochastic optimization
    • time-varying parameters
    • numerical experiments

    Fingerprint

    Dive into the research topics of 'Comparison of Policy Functions from the Optimal Learning and Adaptive Control Frameworks'. Together they form a unique fingerprint.

    Cite this