U-Check: Model Checking and Parameter Synthesis Under Uncertainty

  • Luca Bortolussi
  • Dimitrios Milios
  • Guido Sanguinetti
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9259)


Novel applications of formal modelling such as systems biology have highlighted the need to extend formal analysis techniques to domains with pervasive parametric uncertainty. Consequently, machine learning methods for parameter synthesis and uncertainty quantification are playing an increasingly significant role in quantitative formal modelling. In this paper, we introduce a toolbox for parameter synthesis and model checking in uncertain systems based on Gaussian Process emulation and optimisation. The toolbox implements in a user friendly way the techniques described in a series of recent papers at QEST and other primary venues, and it interfaces easily with widely used modelling languages such as PRISM and Bio-PEPA. We describe in detail the architecture and use of the software, demonstrating its application on a case study.


Model Check Gaussian Process Linear Temporal Logic Radial Basis Function Kernel Parameter Synthesis 
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 International Publishing Switzerland 2015

Authors and Affiliations

  • Luca Bortolussi
    • 1
    • 2
    • 3
  • Dimitrios Milios
    • 4
  • Guido Sanguinetti
    • 4
    • 5
  1. 1.Modelling and Simulation GroupUniversity of SaarlandSaarbrückenGermany
  2. 2.Department of Mathematics and GeosciencesUniversity of TriesteTriesteItaly
  3. 3.CNR/ISTIPisaItaly
  4. 4.School of InformaticsUniversity of EdinburghEdinburghScotland
  5. 5.SynthSys, Centre for Synthetic and Systems BiologyUniversity of EdinburghEdinburghScotland

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