Approximating Labelled Markov Processes Again!

  • Philippe Chaput
  • Vincent Danos
  • Prakash Panangaden
  • Gordon Plotkin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5728)

Abstract

Labelled Markov processes are continuous-state fully probabilistic labelled transition systems. They can be seen as co-algebras of a suitable monad on the category of measurable space. The theory as developed so far included a treatment of bisimulation, logical characterization of bisimulation, weak bisimulation, metrics, universal domains for LMPs and approximations. Much of the theory involved delicate properties of analytic spaces.

Recently a new kind of averaging procedure was used to construct approximations. Remarkably, this version of the theory uses a dual view of LMPs and greatly simplifies the theory eliminating the need to consider aanlytic spaces. In this talk I will survey some of the ideas that led to this work.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Philippe Chaput
    • 1
  • Vincent Danos
    • 2
  • Prakash Panangaden
    • 1
  • Gordon Plotkin
    • 2
  1. 1.School of Computer ScienceMcGill UniversityCanada
  2. 2.School of InformaticsUniversity of EdinburghUK

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