Italo Napolitano

PhD student

Short Bio

Italo Napolitano is a Ph.D. student in Modeling and Engineering Risk and Complexity at Scuola Superiore Meridionale.

He graduated in Automation and Robotics Engineering in October 2023 from the University of Naples Federico II, where he completed a research thesis on learning-based strategies for multi-agent shepherding control problem, under the supervision of Prof. Mario di Bernardo.

His current research focuses on control of multi-agent systems across scales using learning-based methods and optimal transport techniques. His Ph.D. project, titled "Machine-Learning-Based Control of Complex Multi-Agent Systems for Search and Rescue Operations in Natural Disasters," is supervised by Prof. Mario di Bernardo (University of Naples Federico II), Prof. Mirco Musolesi (University College London), Prof. Giovanni Russo (University of Salerno), and Prof. Michael Richardson (Macquarie University). 

Publications

Journal papers:

• I. Napolitano*, S. Covone*, A. Lama, F. De Lellis and M. di Bernardo, "Hierarchical Learning-Based Control for Multiagent Shepherding of Stochastic Autonomous Agents," IEEE Transactions on Control Systems Technology, vol. 34, no. 5, pp. 2179-2190, 2026.

Conference proceedings:

• L. Catello, I. Napolitano, D. Salzano, M. di Bernardo, "Sparse shepherding control of large-scale multi-agent systems via Reinforcement Learning" 24th European Control Conference (ECC), Reykjavík, Iceland, 2026, pp. 2020-2025.

• I. Napolitano, A. Lama, F. De Lellis, M. di Bernardo, "Emergent Cooperative Strategies for Multi-Agent Shepherding via Reinforcement Learning", 23rd European Control Conference (ECC), Thessaloniki, Greece, 2025, pp. 1809-1814.

• S. Covone, I. Napolitano, F. De Lellis, M. di Bernardo, “Hierarchical Policy-Gradient Reinforcement Learning for Multi-Agent Shepherding Control of Non-Cohesive Targets", IEEE 64th Conference on Decision and Control, pp. 3121-3126, 2025.

Preprints:

• I. Napolitano, M. di Bernardo, "Entropy-Regularized Optimal Transport for Time-Varying Multi-Agent Coverage Control," submitted to IEEE Control Systems Letters and American Control Conference, 2026.

• A. Eldesoukey, Md Z. Haider, I. Napolitano, Y. Chen, A. Halder, "Schrödinger Bridges over Kinetic Swarming Models," 2026

• I. Napolitano, M. di Bernardo, "Semi-discrete Optimal Transport for Time-Varying Multi-Agent Coverage Control," submitted to Automatica, 2026.

• C. Punzo, I. Napolitano*, C. Tomaselli*, M. di Bernardo, "Decentralized Shepherding of Non-Cohesive Swarms Through Cluttered Environments via Deep Reinforcement Learning", arXiv, 2025.

*Authors contributed equally