On Reduction Criteria for Probabilistic Reward Models

  • Marcus Größer
  • Gethin Norman
  • Christel Baier
  • Frank Ciesinski
  • Marta Kwiatkowska
  • David Parker
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4337)


In recent papers, the partial order reduction approach has been adapted to reason about the probabilities for temporal properties in concurrent systems with probabilistic behaviours. This paper extends these results by presenting reduction criteria for a probabilistic branching time logic that allows specification of constraints on quantitative measures given by a reward or cost function for the actions of the system.


Model Check Markov Decision Process Reward Structure Reduction Criterion Discount Reward 
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

  • Marcus Größer
    • 1
  • Gethin Norman
    • 2
  • Christel Baier
    • 1
  • Frank Ciesinski
    • 1
  • Marta Kwiatkowska
    • 2
  • David Parker
    • 2
  1. 1.Institut für Informatik IUniversität BonnGermany
  2. 2.School of Computer ScienceUniversity of BirminghamEdgbastonUnited Kingdom

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