Approximating Markov processes through filtration

  • Authors:
  • Chunlai Zhou;Mingsheng Ying

  • Affiliations:
  • Department of Computer Science and Technology, School of Information, Renmin University of China, Beijing 100072, China;State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Lab for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijin ...

  • Venue:
  • Theoretical Computer Science
  • Year:
  • 2012

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Abstract

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.