Deep Learning for Temporal Logics
Frederik Schmitt, Christopher Hahn, Jens U. Kreber, Markus N. Rabe, Bernd Finkbeiner
Temporal logics are a well established formal speciļ¬cation paradigm to specify the behavior of systems, and serve as inputs to industrial-strength veriļ¬cation 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 (AITP 2021).