Propagating Uncertainty in Reinforcement Learning via Wasserstein Barycenters. - Alberto Maria Metelli; Amarildo Likmeta; Marcello Restelli (NeurIPS, 2019)

Truly Batch Model-Free Inverse Reinforcement Learning about Multiple Intentions. - Giorgia Ramponi; Amarildo Likmeta; Alberto Maria Metelli; Andrea Tirinzoni; Marcello Restelli (AISTATS, 2020)

Combining reinforcement learning with rule-based controllers for transparent and general decision-making in autonomous driving. - Amarildo Likmeta; Alberto Maria Metelli; Andrea Tirinzoni; Riccardo Giol; Marcello Restelli; Danilo Romano (Robotics Auton. Syst., 2020)

Monte carlo tree search for trading and hedging. - Edoardo Vittori; Amarildo Likmeta; Marcello Restelli (ICAIF, 2021)

Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems. - Amarildo Likmeta; Alberto Maria Metelli; Giorgia Ramponi; Andrea Tirinzoni; Matteo Giuliani; Marcello Restelli (Mach. Learn., 2021)

Goal-Directed Planning via Hindsight Experience Replay. - Lorenzo Moro; Amarildo Likmeta; Enrico Prati; Marcello Restelli (ICLR, 2022)

Wasserstein Actor-Critic: Directed Exploration via Optimism for Continuous-Actions Control. - Amarildo Likmeta; Matteo Sacco; Alberto Maria Metelli; Marcello Restelli (AAAI, 2023)

A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics. - Puze Liu; Jonas Günster; Niklas Funk; Simon Gröger; Dong Chen; Haitham Bou-Ammar; Julius Jankowski; Ante Maric; Sylvain Calinon; Andrej Orsula; Miguel S. Olivares-Méndez; Hongyi Zhou; et al. (NeurIPS, 2024)