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A Characterization of Meaningful Schedulers for Continuous-Time Markov Decision Processes

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4202))

Abstract

Continuous-time Markov decision process are an important variant of labelled transition systems having nondeterminism through labels and stochasticity through exponential fire-time distributions. Nondeterministic choices are resolved using the notion of a scheduler. In this paper we characterize the class of measurable schedulers, which is the most general one, and show how a measurable scheduler induces a unique probability measure on the sigma-algebra of infinite paths. We then give evidence that for particular reachability properties it is sufficient to consider a subset of measurable schedulers. Having analyzed schedulers and their induced probability measures we finally show that each probability measure on the sigma-algebra of infinite paths is indeed induced by a measurable scheduler which proves that this class is complete.

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Wolovick, N., Johr, S. (2006). A Characterization of Meaningful Schedulers for Continuous-Time Markov Decision Processes. In: Asarin, E., Bouyer, P. (eds) Formal Modeling and Analysis of Timed Systems. FORMATS 2006. Lecture Notes in Computer Science, vol 4202. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11867340_25

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  • DOI: https://doi.org/10.1007/11867340_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45026-9

  • Online ISBN: 978-3-540-45031-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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