30 juin 2022
14:45 - 15:30
Amphithéâtre Guillaume Budé, Site Marcelin Berthelot
En libre accès


Guillaume Baudart, Inria
URL de la vidéo

Synchronous modeling is at the heart of programming languages like Lustre, Esterel, or SCADE used routinely for implementing safety critical control software, e.g., fly-by-wire and engine control in planes. However, to date these languages have had limited modern support for modeling uncertainty — probabilistic aspects of the software’s environment or behavior — even though modeling uncertainty is a primary activity when designing a control system.

In this talk, we present ProbZelus, a synchronous probabilistic programming language. ProbZelus conservatively provides the facilities of a synchronous language to write control software as stream processors, with probabilistic constructs to model uncertainties and perform inference-in-the-loop. We discuss the design an semantics of the language, and propose a semi-symbolic inference algorithm based on delayed sampling for efficient streaming inference. We also present a static analysis that can check if a ProbZelus program will execute in bounded memory under delayed sampling, a key property for reactive systems which never stop.

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