M2 course proposal: Graphs, Machines and Logic

Lecturers

General description

This course explores various connections between computational models and logical frameworks. Starting with classical equivalences from regular language theory, the course will go towards recent results. We will show how understanding the links between logics and computational models such as automata or graph neural networks allow to get a better grasp of the objects at hand, in particular obtain decidability, complexity and expressivity results. On the one hand, computational models allow to decide certain logics, and on the other hand, logics allow to characterize expressivity of computational models.

Prerequisites

There are no specific prerequisites apart from basic knowledge of logic, computational complexity, graphs, and automata.

Organization

Tentative outline

Automata and logic (Denis Kuperberg)

Algorithmic meta-theorem such as Courcelle’s theorem (Édouard Bonnet & Stéphan Thomassé)

Graph Neural Networks and logics with counting (François Schwarzentruber)

Evaluation modalities

There will be an exam at the end of the course, one homework, and an exercise preparing for literature review.