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Precise Parameter Synthesis for Generalised Stochastic Petri Nets with Interval Parameters

  • Milan ČeškaJr.Email author
  • Milan Češka
  • Nicola Paoletti
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10672)

Abstract

We consider the problem of synthesising parameters affecting transition rates and probabilities in generalised Stochastic Petri Nets (GSPNs). Given a time-bounded property expressed as a probabilisitic temporal logic formula, our method allows computing the parameters values for which the probability of satisfying the property meets a given bound, or is optimised. We develop algorithms based on reducing the parameter synthesis problem for GSPNs to the corresponding problem for continuous-time Markov Chains (CTMCs), for which we can leverage existing synthesis algorithms, while retaining the modelling capabilities and expressive power of GSPNs. We evaluate the usefulness of our approach by synthesising parameters for two case studies.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Milan ČeškaJr.
    • 1
    Email author
  • Milan Češka
    • 1
  • Nicola Paoletti
    • 2
  1. 1.Faculty of Information TechnologyBrno University of TechnologyBrnoCzech Republic
  2. 2.Department of Computer ScienceStony Brook UniversityStony BrookUSA

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