| A network model of Italy shows that intermittent regional strategies can alleviate the COVID-19 epidemic F Della Rossa, D Salzano, A Di Meglio, F De Lellis, M Coraggio, ... Nature communications 11 (1), 5106, 2020 | 208 | 2020 |
| Intermittent yet coordinated regional strategies can alleviate the COVID-19 epidemic: a network model of the Italian case F Della Rossa, D Salzano, A Di Meglio, F De Lellis, M Coraggio, ... arXiv preprint arXiv:2005.07594, 2020 | 12 | 2020 |
| Control-tutored reinforcement learning: Towards the integration of data-driven and model-based control F De Lellis, M Coraggio, G Russo, M Musolesi, M Di Bernardo Learning for Dynamics and Control Conference, 1048-1059, 2022 | 7 | 2022 |
| Tutoring reinforcement learning via feedback control F De Lellis, G Russo, M Di Bernardo 2021 European Control Conference (ECC), 580-585, 2021 | 6 | 2021 |
| CT-DQN: Control-tutored deep reinforcement learning F De Lellis, M Coraggio, G Russo, M Musolesi, M dI Bernardo Learning for Dynamics and Control Conference, 941-953, 2023 | 4 | 2023 |
| An application of control-tutored reinforcement learning to the herding problem F De Lellis, F Auletta, G Russo, P de Lellis, M di Bernardo 2021 17th International Workshop on Cellular Nanoscale Networks and their …, 2021 | 4 | 2021 |
| Control-tutored reinforcement learning F De Lellis, F Auletta, G Russo, P De Lellis, M di Bernardo arXiv preprint arXiv:1912.06085, 2019 | 3 | 2019 |
| Guaranteeing control requirements via reward shaping in reinforcement learning F De Lellis, M Coraggio, G Russo, M Musolesi, M di Bernardo IEEE Transactions on Control Systems Technology, 2024 | 2 | 2024 |
| Intermittent non-pharmaceutical strategies to mitigate the COVID-19 epidemic in a network model of Italy via constrained optimization M Coraggio, S Xie, F De Lellis, G Russo, M Di Bernardo 2021 60th IEEE Conference on Decision and Control (CDC), 3538-3543, 2021 | 2 | 2021 |
| Learning-based cognitive architecture for enhancing coordination in human groups A Grotta, M Coraggio, A Spallone, F De Lellis, M di Bernardo arXiv preprint arXiv:2406.06297, 2024 | 1 | 2024 |
| External control of a genetic toggle switch via Reinforcement Learning SM Brancato, F De Lellis, D Salzano, G Russo, M Di Bernardo 2023 European Control Conference (ECC), 1-6, 2023 | 1 | 2023 |
| Emergent Cooperative Strategies for Multi-Agent Shepherding via Reinforcement Learning I Napolitano, A Lama, F De Lellis, M di Bernardo arXiv preprint arXiv:2411.05454, 2024 | | 2024 |
| In vivo learning-based control of microbial populations density in bioreactors SM Brancato, D Salzano, F De Lellis, D Fiore, G Russo, M di Bernardo 6th Annual Learning for Dynamics & Control Conference, 941-953, 2024 | | 2024 |
| Data-driven architecture to encode information in the kinematics of robots and artificial avatars F De Lellis, M Coraggio, NC Foster, R Villa, C Becchio, M di Bernardo arXiv preprint arXiv:2403.06557, 2024 | | 2024 |
Mario di BernardoUniversità di Napoli Federico IIAdresse e-mail validée de unina.it
