Approximating Markov processes through filtration

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Journal Article
Theoretical Computer Science, 2012, 446 pp. 75 - 97
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In this paper, we define a probabilistic version of filtration and use it to provide a finite approximation of Markov processes. In order to measure the approximation, we employ probability logic to construct the final Markov process and define a metric on the set of Markov processes through this logic. Moreover, we show that the set endowed with this metric is a Polish space. Finally we point to some questions connecting approximation to uniformity and approximate bisimilarity as topics for future research. © 2012 Elsevier B.V. All rights reserved.
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