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

  • Nicolás Wolovick
  • Sven Johr
Part of the Lecture Notes in Computer Science book series (LNCS, 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.

Keywords

Probability Measure Sojourn Time Markov Decision Process Combine Transition Negative Exponential Distribution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Nicolás Wolovick
    • 1
  • Sven Johr
    • 2
  1. 1.Fa.M.A.F.Universidad Nacional de Córdoba, Ciudad UniversitariaCórdobaArgentina
  2. 2.FR 6.2 InformatikUniversität des SaarlandesSaarbrückenGermany

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