Finding path and cycle counting formulae in graphs with Deep Reinforcement Learning

no code implementations • 2 Oct 2024 • Jason Piquenot, Maxime Bérar, Pierre Héroux, Jean-Yves Ramel, Romain Raveaux, Sébastien Adam

This paper presents Grammar Reinforcement Learning (GRL), a reinforcement learning algorithm that uses Monte Carlo Tree Search (MCTS) and a transformer architecture that models a Pushdown Automaton (PDA) within a context-free grammar (CFG) framework.

Computational Efficiency reinforcement-learning +1

Technical report: Graph Neural Networks go Grammatical

no code implementations • 2 Mar 2023 • Jason Piquenot, Aldo Moscatelli, Maxime Bérar, Pierre Héroux, Romain Raveaux, Jean-Yves Ramel, Sébastien Adam

This paper introduces a framework for formally establishing a connection between a portion of an algebraic language and a Graph Neural Network (GNN).

Graph Neural Network