4 papers
Generative design of stabilizing controllers with diffusion models: the Youla approach
Matteo Cercola, Donatello Materassi, Simone Formentin
Designing controllers that simultaneously achieve strong performance and provable closed-loop stability remains a central challenge in control engineering. This work introduces a d…
Regularized GLISp for sensor-guided human-in-the-loop optimization
Matteo Cercola, Michele Lomuscio, Dario Piga +1
Human-in-the-loop calibration is often addressed via preference-based optimization, where algorithms learn from pairwise comparisons rather than explicit cost evaluations. While ef…
Efficient Reinforcement Learning from Human Feedback via Bayesian Preference Inference
Matteo Cercola, Valeria Capretti, Simone Formentin
Learning from human preferences is a cornerstone of aligning machine learning models with subjective human judgments. Yet, collecting such preference data is often costly and time-…
Automating the loop in traffic incident management on highway
Matteo Cercola, Nicola Gatti, Pedro Huertas Leyva +2
Effective traffic incident management is essential for ensuring safety, minimizing congestion, and reducing response times in emergency situations. Traditional highway incident man…