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Censoring Markov Chains and Stochastic Bounds

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 4748))

Abstract

We show how to combine censoring technique for Markov chain and strong stochastic comparison to obtain bounds on rewards and the first passage time. We present the main ideas of the method, the algorithms and their proofs. We obtain a substantial reduction of the state space due to the censoring technique. We also present some numerical results to illustrate the effectiveness of the method.

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Katinka Wolter

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© 2007 Springer-Verlag Berlin Heidelberg

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Fourneau, J.M., Pekergin, N., Younès, S. (2007). Censoring Markov Chains and Stochastic Bounds. In: Wolter, K. (eds) Formal Methods and Stochastic Models for Performance Evaluation. EPEW 2007. Lecture Notes in Computer Science, vol 4748. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75211-0_16

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  • DOI: https://doi.org/10.1007/978-3-540-75211-0_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-75210-3

  • Online ISBN: 978-3-540-75211-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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