Enrico Marchesini

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 35

Top Topics

Formal Verification

Robot Navigation

Reinforcement Learning

Partially Observable

Top Venues

Publications

Ayhan Alp Aydeniz, Enrico Marchesini, Christopher Amato, Kagan Tumer
Entropy Seeking Constrained Multiagent Reinforcement Learning. AAMAS (2024)
Luca Marzari, Davide Corsi, Enrico Marchesini, Alessandro Farinelli, Ferdinando Cicalese
Enumerating Safe Regions in Deep Neural Networks with Provable Probabilistic Guarantees. AAAI (2024)
Luca Marzari, Changliu Liu, Priya L. Donti, Enrico Marchesini
Improving Policy Optimization via ε-Retrain. CoRR (2024)
Enrico Marchesini, Christopher Amato
Improving Deep Policy Gradients with Value Function Search. CoRR (2023)
Enrico Marchesini, Luca Marzari, Alessandro Farinelli, Christopher Amato
Safe Deep Reinforcement Learning by Verifying Task-Level Properties. CoRR (2023)
Luca Marzari, Enrico Marchesini, Alessandro Farinelli
Online Safety Property Collection and Refinement for Safe Deep Reinforcement Learning in Mapless Navigation. CoRR (2023)
Enrico Marchesini, Christopher Amato
Improving Deep Policy Gradients with Value Function Search. ICLR (2023)
Luca Marzari, Enrico Marchesini, Alessandro Farinelli
Online Safety Property Collection and Refinement for Safe Deep Reinforcement Learning in Mapless Navigation. ICRA (2023)
Ayhan Alp Aydeniz, Enrico Marchesini, Robert Tyler Loftin, Kagan Tumer
Entropy Maximization in High Dimensional Multiagent State Spaces. MRS (2023)
Enrico Marchesini, Luca Marzari, Alessandro Farinelli, Christopher Amato
Safe Deep Reinforcement Learning by Verifying Task-Level Properties. AAMAS (2023)
Luca Marzari, Davide Corsi, Enrico Marchesini, Alessandro Farinelli, Ferdinando Cicalese
Enumerating Safe Regions in Deep Neural Networks with Provable Probabilistic Guarantees. CoRR (2023)
Maddalena Zuccotto, Marco Piccinelli, Alberto Castellini, Enrico Marchesini, Alessandro Farinelli
Learning State-Variable Relationships in POMCP: A Framework for Mobile Robots. Frontiers Robotics AI 9 (2022)
Luca Marzari, Davide Corsi, Enrico Marchesini, Alessandro Farinelli
Curriculum learning for safe mapless navigation. SAC (2022)
Enrico Marchesini, Davide Corsi, Alessandro Farinelli
Exploring Safer Behaviors for Deep Reinforcement Learning. AAAI (2022)
Enrico Marchesini, Alessandro Farinelli
Enhancing Deep Reinforcement Learning Approaches for Multi-Robot Navigation via Single-Robot Evolutionary Policy Search. ICRA (2022)
Enrico Marchesini, Christopher Amato
Safety-informed mutations for evolutionary deep reinforcement learning. GECCO Companion (2022)
Maddalena Zuccotto, Marco Piccinelli, Alberto Castellini, Enrico Marchesini, Alessandro Farinelli
Learning State-Variable Relationships in POMCP: A Framework for Mobile Robots. Future Internet 9 (2022)
Enrico Marchesini, Alessandro Farinelli
Centralizing State-Values in Dueling Networks for Multi-Robot Reinforcement Learning Mapless Navigation. IROS (2021)
Alberto Castellini, Enrico Marchesini, Alessandro Farinelli
Partially Observable Monte Carlo Planning with state variable constraints for mobile robot navigation. Eng. Appl. Artif. Intell. 104 (2021)
Ameya Pore, Davide Corsi, Enrico Marchesini, Diego Dall'Alba, Alicia Casals, Alessandro Farinelli, Paolo Fiorini
Safe Reinforcement Learning using Formal Verification for Tissue Retraction in Autonomous Robotic-Assisted Surgery. IROS (2021)
Enrico Marchesini, Alessandro Farinelli
Centralizing State-Values in Dueling Networks for Multi-Robot Reinforcement Learning Mapless Navigation. CoRR (2021)
Luca Marzari, Davide Corsi, Enrico Marchesini, Alessandro Farinelli
Curriculum Learning for Safe Mapless Navigation. CoRR (2021)
Davide Corsi, Enrico Marchesini, Alessandro Farinelli
Formal verification of neural networks for safety-critical tasks in deep reinforcement learning. UAI (2021)
Ameya Pore, Davide Corsi, Enrico Marchesini, Diego Dall'Alba, Alicia Casals, Alessandro Farinelli, Paolo Fiorini
Safe Reinforcement Learning using Formal Verification for Tissue Retraction in Autonomous Robotic-Assisted Surgery. CoRR (2021)
Enrico Marchesini, Davide Corsi, Alessandro Farinelli
Benchmarking Safe Deep Reinforcement Learning in Aquatic Navigation. CoRR (2021)
Enrico Marchesini, Davide Corsi, Alessandro Farinelli
Benchmarking Safe Deep Reinforcement Learning in Aquatic Navigation. IROS (2021)
Enrico Marchesini, Davide Corsi, Alessandro Farinelli
Genetic Soft Updates for Policy Evolution in Deep Reinforcement Learning. ICLR (2021)
Maddalena Zuccotto, Alberto Castellini, Marco Piccinelli, Enrico Marchesini, Alessandro Farinelli
Learning Environment Properties in Partially Observable Monte Carlo Planning. AIRO@AI*IA (2021)
Davide Corsi, Enrico Marchesini, Alessandro Farinelli
Evaluating the Safety of Deep Reinforcement Learning Models using Semi-Formal Verification. CoRR (2020)
Enrico Marchesini, Alessandro Farinelli
Discrete Deep Reinforcement Learning for Mapless Navigation. ICRA (2020)
Davide Corsi, Enrico Marchesini, Alessandro Farinelli, Paolo Fiorini
Formal Verification for Safe Deep Reinforcement Learning in Trajectory Generation. IRC (2020)
Enrico Marchesini, Alessandro Farinelli
Genetic Deep Reinforcement Learning for Mapless Navigation. AAMAS (2020)
Alberto Castellini, Enrico Marchesini, Giulio Mazzi, Alessandro Farinelli
Explaining the Influence of Prior Knowledge on POMCP Policies. EUMAS/AT (2020)
Alberto Castellini, Enrico Marchesini, Alessandro Farinelli
Online Monte Carlo Planning for Autonomous Robots: Exploiting Prior Knowledge on Task Similarities. AIRO@AI*IA (2019)
Enrico Marchesini, Davide Corsi, Andrea Benfatti, Alessandro Farinelli, Paolo Fiorini
Double Deep Q-Network for Trajectory Generation of a Commercial 7DOF Redundant Manipulator. IRC (2019)