Francesco De Lellis

According to our database, Francesco De Lellis authored at least 17 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Hierarchical Learning-Based Control for Multi-Agent Shepherding of Stochastic Autonomous Agents.

Italo Napolitano, Stefano Covone, Andrea Lama, Francesco De Lellis, Mario di Bernardo

CoRR, August, 2025

Breaking the mould of Social Mixed Reality - State-of-the-Art and Glossary.

Marta Bienkiewicz, Julia Ayache, Panayiotis Charalambous, Cristina Becchio, Marco Corragio, Bertram Taetz, Francesco De Lellis, Antonio Grotta, Anna Server, Daniel Rammer, Richard Kulpa, Franck Multon, Azucena García-Palacios, Jessica Sutherland, Kathleen Bryson, Stéphane Donikian, Didier Stricker, Benoît G. Bardy

CoRR, July, 2025

Online Phase Estimation of Human Oscillatory Motions using Deep Learning.

Antonio Grotta, Francesco De Lellis

CoRR, May, 2025

Hierarchical Policy-Gradient Reinforcement Learning for Multi-Agent Shepherding Control of Non-Cohesive Targets.

Stefano Covone, Italo Napolitano, Francesco De Lellis, Mario di Bernardo

CoRR, April, 2025

Emergent Cooperative Strategies for Multi-Agent Shepherding via Reinforcement Learning.

Italo Napolitano, Andrea Lama, Francesco De Lellis, Mario di Bernardo

Proceedings of the 2025 European Control Conference, 2025

2024

Guaranteeing Control Requirements via Reward Shaping in Reinforcement Learning.

Francesco De Lellis, Marco Coraggio, Giovanni Russo, Mirco Musolesi, Mario di Bernardo

IEEE Trans. Control. Syst. Technol., November, 2024

Data-Driven Architecture to Encode Information in the Kinematics of Robots and Artificial Avatars.

Francesco De Lellis, Marco Coraggio, Nathan C. Foster, Riccardo Villa, Cristina Becchio, Mario di Bernardo

IEEE Control. Syst. Lett., 2024

Learning-based cognitive architecture for enhancing coordination in human groups.

Antonio Grotta, Marco Coraggio, Antonio Spallone, Francesco De Lellis, Mario di Bernardo

CoRR, 2024

In vivo learning-based control of microbial populations density in bioreactors.

Sara Maria Brancato, Davide Salzano, Francesco De Lellis, Davide Fiore, Giovanni Russo, Mario di Bernardo

Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

2023

CT-DQN: Control-Tutored Deep Reinforcement Learning.

Francesco De Lellis, Marco Coraggio, Giovanni Russo, Mirco Musolesi, Mario di Bernardo

Proceedings of the Learning for Dynamics and Control Conference, 2023

External control of a genetic toggle switch via Reinforcement Learning.

Sara Maria Brancato, Francesco De Lellis, Davide Salzano, Giovanni Russo, Mario di Bernardo

Proceedings of the European Control Conference, 2023

2022

CT-DQN: Control-Tutored Deep Reinforcement Learning.

Francesco De Lellis, Marco Coraggio, Giovanni Russo, Mirco Musolesi, Mario di Bernardo

CoRR, 2022

Control-Tutored Reinforcement Learning: Towards the Integration of Data-Driven and Model-Based Control.

Francesco De Lellis, Marco Coraggio, Giovanni Russo, Mirco Musolesi, Mario di Bernardo

Proceedings of the Learning for Dynamics and Control Conference, 2022

2021

Tutoring Reinforcement Learning via Feedback Control.

Francesco De Lellis, Giovanni Russo, Mario di Bernardo

Proceedings of the 2021 European Control Conference, 2021

Intermittent non-pharmaceutical strategies to mitigate the COVID-19 epidemic in a network model of Italy via constrained optimization.

Marco Coraggio, Shihao Xie, Francesco De Lellis, Giovanni Russo, Mario di Bernardo

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2019

Control-Tutored Reinforcement Learning.

Francesco De Lellis, Fabrizia Auletta, Giovanni Russo, Pietro De Lellis, Mario di Bernardo

CoRR, 2019

Control-Tutored Reinforcement Learning: an application to the Herding Problem.

Francesco De Lellis, Fabrizia Auletta, Giovanni Russo, Mario di Bernardo

CoRR, 2019