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    政大機構典藏 > 理學院 > 應用數學系 > 學位論文 >  Item 140.119/88735
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/88735

    Title: 非均質馬可夫決策系統的決策空間
    Policies in Nonhomogeneous Markov Decision Processes
    Authors: 劉任昌
    Liou, Chen Chang
    Contributors: 陸行
    Paul Lu
    Liou, Chen Chang
    Keywords: 非均質馬可夫決策系統
    Nonhomogeneous Markov Processes
    Date: 1994
    Issue Date: 2016-04-29 16:32:18 (UTC+8)
    Abstract:   在求無限期非均質馬可夫決策過程(nonhomogeneous Markov decisinon processes)第一期的的最佳解時,我們通常要將它表示成有限期的動態規劃問題。動態規劃可以用合成函數型式表示,也可以用最常見的線性規劃型式表示。
      Hopp, Bean and Duenyas(1992) formulate a mixed integer program (MIP) to determine whether a finite time horizon is a forecast horizon in a nonhomogeneous Markov decision process(NMDP). Their formula are solved by complex Bender's decomposition In this thesis, we make an examination in details of the contraction property and affine mapping property of NMDP. By these properties we are relieved of the complex MIP formula and Bender's decomposition algorithm. The main contribution of the thesis is to show that it is not necessary to determine the optimal policies by running through the whole feasible solution space of their MIP problem. We only need to check a finite number of vertices at a polyhedral set shaped by the solution of the NMDP. The analysis shows insights into the NMDP and facilitate the prosess in determining the forecast horizon. Furthermore, this NMDP formulation is presented in the form of a simple dynamic function which is different from the linear program presented by Hopp, Bean and Duenyas.
    Description: 碩士
    Source URI: http://thesis.lib.nccu.edu.tw/record/#B2002003903
    Data Type: thesis
    Appears in Collections:[應用數學系] 學位論文

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