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ORCIDEnrico Marchesini
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2020 – today
- 2024
[c22]Luca Marzari, Davide Corsi, Enrico Marchesini, Alessandro Farinelli, Ferdinando Cicalese:
Enumerating Safe Regions in Deep Neural Networks with Provable Probabilistic Guarantees. AAAI 2024: 21387-21394- [c21]Ayhan Alp Aydeniz, Enrico Marchesini, Christopher Amato, Kagan Tumer:
Entropy Seeking Constrained Multiagent Reinforcement Learning. AAMAS 2024: 2141-2143 - [i12]Luca Marzari, Changliu Liu, Priya L. Donti, Enrico Marchesini:
Improving Policy Optimization via ε-Retrain. CoRR abs/2406.08315 (2024) - [i11]Enrico Marchesini, Andrea Baisero, Rupali Bathi, Christopher Amato:
On Stateful Value Factorization in Multi-Agent Reinforcement Learning. CoRR abs/2408.15381 (2024) - [i10]Ayhan Alp Aydeniz, Enrico Marchesini, Robert Tyler Loftin, Christopher Amato, Kagan Tumer:
Safe Multiagent Coordination via Entropic Exploration. CoRR abs/2412.20361 (2024) - 2023
- [c20]Enrico Marchesini, Luca Marzari, Alessandro Farinelli, Christopher Amato:
Safe Deep Reinforcement Learning by Verifying Task-Level Properties. AAMAS 2023: 1466-1475 - [c19]Enrico Marchesini, Christopher Amato:
Improving Deep Policy Gradients with Value Function Search. ICLR 2023 - [c18]Luca Marzari, Enrico Marchesini
, Alessandro Farinelli:
Online Safety Property Collection and Refinement for Safe Deep Reinforcement Learning in Mapless Navigation. ICRA 2023: 7133-7139 - [c17]Ayhan Alp Aydeniz, Enrico Marchesini, Robert Tyler Loftin, Kagan Tumer:
Entropy Maximization in High Dimensional Multiagent State Spaces. MRS 2023: 92-99 - [i9]Luca Marzari, Enrico Marchesini, Alessandro Farinelli:
Online Safety Property Collection and Refinement for Safe Deep Reinforcement Learning in Mapless Navigation. CoRR abs/2302.06695 (2023) - [i8]Enrico Marchesini, Luca Marzari, Alessandro Farinelli, Christopher Amato:
Safe Deep Reinforcement Learning by Verifying Task-Level Properties. CoRR abs/2302.10030 (2023) - [i7]Enrico Marchesini, Christopher Amato:
Improving Deep Policy Gradients with Value Function Search. CoRR abs/2302.10145 (2023) - [i6]Luca Marzari, Davide Corsi, Enrico Marchesini, Alessandro Farinelli, Ferdinando Cicalese:
Enumerating Safe Regions in Deep Neural Networks with Provable Probabilistic Guarantees. CoRR abs/2308.09842 (2023) - 2022
- [j2]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) - [c16]Enrico Marchesini, Davide Corsi, Alessandro Farinelli:
Exploring Safer Behaviors for Deep Reinforcement Learning. AAAI 2022: 7701-7709 - [c15]Enrico Marchesini, Christopher Amato:
Safety-informed mutations for evolutionary deep reinforcement learning. GECCO Companion 2022: 1966-1970 - [c14]Enrico Marchesini, Alessandro Farinelli:
Enhancing Deep Reinforcement Learning Approaches for Multi-Robot Navigation via Single-Robot Evolutionary Policy Search. ICRA 2022: 5525-5531 - [c13]Luca Marzari, Davide Corsi, Enrico Marchesini, Alessandro Farinelli:
Curriculum learning for safe mapless navigation. SAC 2022: 766-769 - 2021
- [j1]Alberto Castellini, Enrico Marchesini, Alessandro Farinelli:
Partially Observable Monte Carlo Planning with state variable constraints for mobile robot navigation. Eng. Appl. Artif. Intell. 104: 104382 (2021) - [c12]Maddalena Zuccotto, Alberto Castellini, Marco Piccinelli, Enrico Marchesini, Alessandro Farinelli:
Learning Environment Properties in Partially Observable Monte Carlo Planning. AIRO@AI*IA 2021: 50-57 - [c11]Enrico Marchesini, Davide Corsi, Alessandro Farinelli:
Genetic Soft Updates for Policy Evolution in Deep Reinforcement Learning. ICLR 2021 - [c10]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: 4025-4031 - [c9]Enrico Marchesini, Alessandro Farinelli:
Centralizing State-Values in Dueling Networks for Multi-Robot Reinforcement Learning Mapless Navigation. IROS 2021: 4583-4588 - [c8]Enrico Marchesini, Davide Corsi, Alessandro Farinelli:
Benchmarking Safe Deep Reinforcement Learning in Aquatic Navigation. IROS 2021: 5590-5595 - [c7]Davide Corsi, Enrico Marchesini, Alessandro Farinelli:
Formal verification of neural networks for safety-critical tasks in deep reinforcement learning. UAI 2021: 333-343 - [i5]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 abs/2109.02323 (2021) - [i4]Enrico Marchesini, Alessandro Farinelli:
Centralizing State-Values in Dueling Networks for Multi-Robot Reinforcement Learning Mapless Navigation. CoRR abs/2112.09012 (2021) - [i3]Enrico Marchesini, Davide Corsi, Alessandro Farinelli:
Benchmarking Safe Deep Reinforcement Learning in Aquatic Navigation. CoRR abs/2112.10593 (2021) - [i2]Luca Marzari, Davide Corsi, Enrico Marchesini, Alessandro Farinelli:
Curriculum Learning for Safe Mapless Navigation. CoRR abs/2112.12490 (2021) - 2020
- [c6]Enrico Marchesini, Alessandro Farinelli:
Genetic Deep Reinforcement Learning for Mapless Navigation. AAMAS 2020: 1919-1921 - [c5]Alberto Castellini, Enrico Marchesini, Giulio Mazzi, Alessandro Farinelli:
Explaining the Influence of Prior Knowledge on POMCP Policies. EUMAS/AT 2020: 261-276 - [c4]Enrico Marchesini, Alessandro Farinelli:
Discrete Deep Reinforcement Learning for Mapless Navigation. ICRA 2020: 10688-10694 - [c3]Davide Corsi, Enrico Marchesini, Alessandro Farinelli, Paolo Fiorini:
Formal Verification for Safe Deep Reinforcement Learning in Trajectory Generation. IRC 2020: 352-359 - [i1]Davide Corsi, Enrico Marchesini, Alessandro Farinelli:
Evaluating the Safety of Deep Reinforcement Learning Models using Semi-Formal Verification. CoRR abs/2010.09387 (2020)
2010 – 2019
- 2019
- [c2]Alberto Castellini, Enrico Marchesini, Alessandro Farinelli:
Online Monte Carlo Planning for Autonomous Robots: Exploiting Prior Knowledge on Task Similarities. AIRO@AI*IA 2019: 25-32 - [c1]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: 421-422
Coauthor Index
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