Online Monte Carlo Planning for Autonomous Robots: Exploiting Prior Knowledge on Task Similarities. - Alberto Castellini; Enrico Marchesini; Alessandro Farinelli (AIRO@AI*IA, 2019)

Double Deep Q-Network for Trajectory Generation of a Commercial 7DOF Redundant Manipulator. - Enrico Marchesini; Davide Corsi; Andrea Benfatti; Alessandro Farinelli; Paolo Fiorini (IRC, 2019)

Genetic Deep Reinforcement Learning for Mapless Navigation. - Enrico Marchesini; Alessandro Farinelli (AAMAS, 2020)

Explaining the Influence of Prior Knowledge on POMCP Policies. - Alberto Castellini; Enrico Marchesini; Giulio Mazzi; Alessandro Farinelli (EUMAS/AT, 2020)

Discrete Deep Reinforcement Learning for Mapless Navigation. - Enrico Marchesini; Alessandro Farinelli (ICRA, 2020)

Formal Verification for Safe Deep Reinforcement Learning in Trajectory Generation. - Davide Corsi; Enrico Marchesini; Alessandro Farinelli; Paolo Fiorini (IRC, 2020)

Evaluating the Safety of Deep Reinforcement Learning Models using Semi-Formal Verification. - Davide Corsi; Enrico Marchesini; Alessandro Farinelli (CoRR, 2020)

Learning Environment Properties in Partially Observable Monte Carlo Planning. - Maddalena Zuccotto; Alberto Castellini; Marco Piccinelli; Enrico Marchesini; Alessandro Farinelli (AIRO@AI*IA, 2021)

Genetic Soft Updates for Policy Evolution in Deep Reinforcement Learning. - Enrico Marchesini; Davide Corsi; Alessandro Farinelli (ICLR, 2021)

Benchmarking Safe Deep Reinforcement Learning in Aquatic Navigation. - Enrico Marchesini; Davide Corsi; Alessandro Farinelli (IROS, 2021)

Centralizing State-Values in Dueling Networks for Multi-Robot Reinforcement Learning Mapless Navigation. - Enrico Marchesini; Alessandro Farinelli (IROS, 2021)

Safe Reinforcement Learning using Formal Verification for Tissue Retraction in Autonomous Robotic-Assisted Surgery. - Ameya Pore; Davide Corsi; Enrico Marchesini; Diego Dall'Alba; Alicia Casals; Alessandro Farinelli; Paolo Fiorini (IROS, 2021)

Formal verification of neural networks for safety-critical tasks in deep reinforcement learning. - Davide Corsi; Enrico Marchesini; Alessandro Farinelli (UAI, 2021)

Partially Observable Monte Carlo Planning with state variable constraints for mobile robot navigation. - Alberto Castellini; Enrico Marchesini; Alessandro Farinelli (Eng. Appl. Artif. Intell., 2021)

Exploring Safer Behaviors for Deep Reinforcement Learning. - Enrico Marchesini; Davide Corsi; Alessandro Farinelli (AAAI, 2022)

Safety-informed mutations for evolutionary deep reinforcement learning. - Enrico Marchesini; Christopher Amato (GECCO Companion, 2022)

Enhancing Deep Reinforcement Learning Approaches for Multi-Robot Navigation via Single-Robot Evolutionary Policy Search. - Enrico Marchesini; Alessandro Farinelli (ICRA, 2022)

Curriculum learning for safe mapless navigation. - Luca Marzari; Davide Corsi; Enrico Marchesini; Alessandro Farinelli (SAC, 2022)

Learning State-Variable Relationships in POMCP: A Framework for Mobile Robots. - Maddalena Zuccotto; Marco Piccinelli; Alberto Castellini; Enrico Marchesini; Alessandro Farinelli (Frontiers Robotics AI, 2022)

Safe Deep Reinforcement Learning by Verifying Task-Level Properties. - Enrico Marchesini; Luca Marzari; Alessandro Farinelli; Christopher Amato (AAMAS, 2023)

Improving Deep Policy Gradients with Value Function Search. - Enrico Marchesini; Christopher Amato (ICLR, 2023)

Online Safety Property Collection and Refinement for Safe Deep Reinforcement Learning in Mapless Navigation. - Luca Marzari; Enrico Marchesini; Alessandro Farinelli (ICRA, 2023)

Entropy Maximization in High Dimensional Multiagent State Spaces. - Ayhan Alp Aydeniz; Enrico Marchesini; Robert Tyler Loftin; Kagan Tumer (MRS, 2023)

Enumerating Safe Regions in Deep Neural Networks with Provable Probabilistic Guarantees. - Luca Marzari; Davide Corsi; Enrico Marchesini; Alessandro Farinelli; Ferdinando Cicalese (AAAI, 2024)

Entropy Seeking Constrained Multiagent Reinforcement Learning. - Ayhan Alp Aydeniz; Enrico Marchesini; Christopher Amato; Kagan Tumer (AAMAS, 2024)

On Stateful Value Factorization in Multi-Agent Reinforcement Learning. - Enrico Marchesini; Andrea Baisero; Rupali Bathi; Christopher Amato (CoRR, 2024)

Safe Multiagent Coordination via Entropic Exploration. - Ayhan Alp Aydeniz; Enrico Marchesini; Robert Tyler Loftin; Christopher Amato; Kagan Tumer (CoRR, 2024)

Safe Entropic Agents under Team Constraints. - Ayhan Alp Aydeniz; Enrico Marchesini; Robert Loftin; Christopher Amato; Kagan Tumer (AAMAS, 2025)

On Stateful Value Factorization in Multi-Agent Reinforcement Learning. - Enrico Marchesini; Andrea Baisero; Rupali Bhati; Christopher Amato (AAMAS, 2025)

Improving Policy Optimization via ε-Retrain. - Luca Marzari; Priya L. Donti; Changliu Liu; Enrico Marchesini (AAMAS, 2025)

RL2Grid: Benchmarking Reinforcement Learning in Power Grid Operations. - Enrico Marchesini; Benjamin Donnot; Constance Crozier; Ian Dytham; Christian Merz; Lars Schewe; Nico Westerbeck; Cathy Wu 002; Antoine Marot; Priya L. Donti (CoRR, 2025)

Designing Control Barrier Function via Probabilistic Enumeration for Safe Reinforcement Learning Navigation. - Luca Marzari; Francesco Trotti; Enrico Marchesini; Alessandro Farinelli (IEEE Robotics Autom. Lett., 2025)