Synthesis of Optimal Feedback Controllers from Data via Stochastic Gradient Descent. - Laura Ferrarotti; Alberto Bemporad (ECC, 2019)

Learning nonlinear feedback controllers from data via optimal policy search and stochastic gradient descent. - Laura Ferrarotti; Alberto Bemporad (CDC, 2020)

The benefits of sharing: a cloud-aided performance-driven framework to learn optimal feedback policies. - Laura Ferrarotti; Valentina Breschi; Alberto Bemporad (L4DC, 2021)

Quantitative and Qualitative Evaluation of Reinforcement Learning Policies for Autonomous Vehicles. - Laura Ferrarotti; Massimiliano Luca; Gabriele Santin; Giorgio Previati; Gianpiero Mastinu; Elena Campi; Lorenzo Uccello; Antonino Albanese; Praveen Zalaya; Alessandro Roccasalva; Bruno Lepri (CoRR, 2023)

Autonomous and Human-Driven Vehicles Interacting in a Roundabout: A Quantitative and Qualitative Evaluation. - Laura Ferrarotti; Massimiliano Luca; Gabriele Santin; Giorgio Previati; Gianpiero Mastinu; Massimiliano Gobbi; Elena Campi; Lorenzo Uccello; Antonino Albanese; Praveen Zalaya; Alessandro Roccasalva; Bruno Lepri (IEEE Access, 2024)

SMoSE: Sparse Mixture of Shallow Experts for Interpretable Reinforcement Learning in Continuous Control Tasks. - Mátyás Vincze; Laura Ferrarotti; Leonardo Lucio Custode; Bruno Lepri; Giovanni Iacca (AAAI, 2025)