Ontology-Mediated Probabilistic Model Checking

Clemens DubslaffClemens Dubslaff, Patrick KoopmannPatrick Koopmann, Anni-Yasmin TurhanAnni-Yasmin Turhan

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Clemens Dubslaff, Patrick Koopmann, Anni-Yasmin Turhan
Ontology-Mediated Probabilistic Model Checking
Proc. of 15th International Conference on integrated Formal Methods, volume 11918 of Lecture Notes in Computer Science, 194--211, 2019. Springer

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KurzfassungAbstract
Probabilistic model checking (PMC) is a well-established method for the quantitative analysis of dynamic systems. Description logics (DLs) provide a well-suited formalism to describe and reason about terminological knowledge, used in many areas to specify background knowledge on the domain. We investigate how such knowledge can be integrated into the PMC process, introducing ontology-mediated PMC. Specifically, we propose a formalism that links ontologies to dynamic behaviors specified by guarded commands, the de-facto standard input formalism for PMC tools such as Prism. Further, we present and implement a technique for their analysis relying on existing DL-reasoning and PMC tools. This way, we enable the application of standard PMC techniques to analyze knowledge-intensive systems. Our approach is implemented and evaluated on a multi-server system case study, where different DL-ontologies are used to provide specifications of different server platforms and situations the system is executed in.
Forschungsgruppe:Research Group: Algebraische und logische Grundlagen der InformatikAlgebraic and Logical Foundations of Computer Science

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-030-34968-4_11.

@inproceedings{DKT2019,
  author    = {Clemens Dubslaff and Patrick Koopmann and Anni-Yasmin Turhan},
  title     = {Ontology-Mediated Probabilistic Model Checking},
  booktitle = {Proc. of 15th International Conference on integrated Formal
               Methods},
  series    = {Lecture Notes in Computer Science},
  volume    = {11918},
  publisher = {Springer},
  year      = {2019},
  pages     = {194--211},
  doi       = {10.1007/978-3-030-34968-4_11}
}