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    A New Adaptive Dynamic Programming Reinforcement Learning Method for Discrete-Time Linear-Quadratic Optimal Control Problems 

    Source: ASME Letters in Dynamic Systems and Control:;2026:;volume( 006 ):;issue:001:;page 140
    Author(s): Xu, Lingyi; López Muro, Juan; Gajić, Zoran
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Abstract. In this article, we present a new policy iteration approach to solve the linear-quadratic (LQ) optimal control problem for infinite horizon discrete-time dynamic systems under the assumption that the system input ...
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    Improving Reinforcement Learning Value Iterations in Discrete-Time Linear-Quadratic Optimal Control 

    Source: Journal of Dynamic Systems, Measurement, and Control:;2026:;volume( 148 ):;issue:001:;page 19
    Author(s): Xu, Lingyi; Gajic, Zoran
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Abstract. The paper demonstrates via simulation that the well-known value iteration algorithm of reinforcement learning for the discrete-time linear-quadratic optimal control problem converges very slowly—at most linearly. ...
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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