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题名:	非均質馬可夫決策系統的決策空間 Policies in Nonhomogeneous Markov Decision Processes
作者:	劉任昌 Liou, Chen Chang
贡献者:	陸行 Paul Lu 劉任昌 Liou, Chen Chang
关键词:	非均質馬可夫決策系統 Nonhomogeneous Markov Processes
日期:	1994
上传时间:	2016-04-29 16:32:18 (UTC+8)
摘要:	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.
描述:	碩士國立政治大學應用數學系 81155006
資料來源:	http://thesis.lib.nccu.edu.tw/record/#B2002003903
数据类型:	thesis
显示于类别:	[應用數學系] 學位論文

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