Deep Learning for Temporal Logics

Frederik Schmitt, Christopher Hahn, Jens Kreber, Markus N. Rabe and Bernd Finkbeiner

Temporal logics are a well established formal specification paradigm to specify the behavior of systems, and serve as inputs to industrial-strength verification tools. We report on current advances in applying deep learning to temporal logical reasoning tasks, showing that models can even solve instances where competitive classical algorithms timed out.

6th Conference on Artificial Intelligence and Theorem Proving September 2021
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