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Title: Stochastic control optimal in the Kullback sense (English)
Author: Šindelář, Jan
Author: Vajda, Igor
Author: Kárný, Miroslav
Language: English
Journal: Kybernetika
ISSN: 0023-5954
Volume: 44
Issue: 1
Year: 2008
Pages: 53-60
Summary lang: English
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Category: math
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Summary: The paper solves the problem of minimization of the Kullback divergence between a partially known and a completely known probability distribution. It considers two probability distributions of a random vector $(u_1, x_1, \ldots, u_T, x_T )$ on a sample space of $2T$ dimensions. One of the distributions is known, the other is known only partially. Namely, only the conditional probability distributions of $x_\tau$ given $u_1, x_1, \ldots, u_{\tau-1}, x_{\tau-1}, u_{\tau}$ are known for $\tau = 1, \ldots, T$. Our objective is to determine the remaining conditional probability distributions of $u_\tau$ given $u_1, x_1, \ldots, u_{\tau-1}, x_{\tau-1}$ such that the Kullback divergence of the partially known distribution with respect to the completely known distribution is minimal. Explicit solution of this problem has been found previously for Markovian systems in Karný [Karny:96a]. The general solution is given in this paper. (English)
Keyword: Kullback divergence
Keyword: minimization
Keyword: stochastic controller
MSC: 49N35
MSC: 60G35
MSC: 90D60
MSC: 91A60
MSC: 93E03
MSC: 93E20
MSC: 94A17
idZBL: Zbl 1145.93053
idMR: MR2405055
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Date available: 2009-09-24T20:32:02Z
Last updated: 2012-06-06
Stable URL: http://hdl.handle.net/10338.dmlcz/135833
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