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Solving Verification Questions using Machine Learning

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Formal verification’s aim is that of deriving rigorous proofs for the correctness of systems and, traditionally, has mainly been tackled using automated reasoning methods. In this talk, I will argue that formal verification can be takled using statistical methods too. I will discuss the liveness verification question which, intuitively, is the question of whether a system always responds. For dynamical systems, this relates to the stability question; for computer programs, it is the halting problem. I will present a novel approach where neural networks are used to learn formal witnesses (ranking and Lyapunov functions) of liveness from data while ensuring formal soundness of these witness. I will show how we apply this method to the stability analysis of dynamical systems and to the termination analysis of probabilistic programs.


Topic: Theory Seminar – Mirco Giacobbe Time: Oct 15, 2021 01:45 PM London

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