Metrics for Labeled Markov Systems

  • Josée Desharnais
  • Vineet Gupta
  • Radha Jagadeesan
  • Prakash Panangaden
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1664)


Partial Labeled Markov Chains (plMc) generalize process algebra and traditional Markov chains. They provide a foundation for interacting discrete probabilistic systems. Existing notions of process equivalence are too sensitive to the exact probabilities of transitions in plMcs. This paper studies more robust notions of “approximate” equivalence between plMcs.


Model Check Functional Expression Start State Parallel Composition Process Algebra 
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 1999

Authors and Affiliations

  • Josée Desharnais
    • 1
  • Vineet Gupta
    • 2
  • Radha Jagadeesan
    • 3
  • Prakash Panangaden
    • 1
  1. 1.School of Computer ScienceMcGill UniversityMontrealCanada
  2. 2.Autonomy and Robotics AreaNASA Ames Research CenterMoffett FieldUSA
  3. 3.Dept. of Math. and Computer SciencesLoyola University-Lake Shore CampusChicagoUSA

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