Adapting an AI Planning Heuristic for Directed Model Checking

  • Sebastian Kupferschmid
  • Jörg Hoffmann
  • Henning Dierks
  • Gerd Behrmann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3925)


There is a growing body of work on directed model checking, which improves the falsification of safety properties by providing heuristic functions that can guide the search quickly towards short error paths. Techniques of this kind have also been made very successful in the area of AI Planning. Our main technical contribution is the adaptation of the most successful heuristic function from AI Planning to the model checking context, yielding a new heuristic for directed model checking. The heuristic is based on solving an abstracted problem in every search state. We adapt the abstraction and its solution to networks of communicating automata annotated with (constraints and effects on) integer variables. Since our ultimate goal in this research is to also take into account clock variables, as used in timed automata, our techniques are implemented inside UPPAAL. We run experiments in some toy benchmarks for timed automata, and in two timed automata case studies originating from an industrial project. Compared to both blind search and some previously proposed heuristic functions, we consistently obtain significant, sometimes dramatic, search space reductions, resulting in likewise strong reductions of runtime and memory requirements.


Model Check Integer Variable Search State Heuristic Function Greedy Search 
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

  • Sebastian Kupferschmid
    • 1
  • Jörg Hoffmann
    • 2
  • Henning Dierks
    • 3
  • Gerd Behrmann
    • 4
  1. 1.University of FreiburgGermany
  2. 2.Max Planck Institute for CSSaarbrückenGermany
  3. 3.OFFISGermany
  4. 4.Aalborg UniversityDenmark

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