Solving Graded/Probabilistic Modal Logic via Linear Inequalities (System Description)

  • William Snell
  • Dirk Pattinson
  • Florian Widmann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7180)

Abstract

We present the experience gained from implementing a new decision procedure for both graded and probabilistic modal logic. While our approach uses standard tableaux for propositional connectives, modal rules are given by linear constraints on the arguments of operators. The implementation uses binary decision diagrams for propositional connectives and a linear programming library for the modal rules. We compare our implementation, for graded modal logic, with other tools, showing average performance. Due to lack of other implementations, no comparison is provided for probabilistic modal logic, the main new feature of our implementation.

Keywords

Modal Logic Description Logic Linear Inequality Modal Rule Propositional Variable 
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 2012

Authors and Affiliations

  • William Snell
    • 1
  • Dirk Pattinson
    • 1
  • Florian Widmann
    • 1
  1. 1.Dept. of ComputingImperial CollegeLondonUK

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