Research activity
Our research was conducted under the auspices of Sapienza University of Rome and Carlos III University of Madrid, from which AI METHODS emerged as a spin-off company.
Scientific Papers
2024
A. Jardines, M. Ponzano, J. García-Heras, et al., “Pre-tactical convection prediction for air traffic flow management using lstm neural network”, Meteorological Applications, vol. 31, no. 3, e2215, 2024
Brunori, D. and Iocchi, L. (2024). A Delay-Aware DRL-Based Environment for Cooperative Multi-UAV Systems in Multi-Purpose Scenarios. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-680-4; ISSN 2184-433X, SciTePress, pages 334-343. DOI: 10.5220/0012347900003636
A. Jardines, H. Eivazi, E. Zea, et al., “Thunderstorm prediction during pre-tactical air-traffic-flow management using convolutional neural networks”, Expert systems with applications, vol. 241, p. 122 466, 2024
I. Martínez, J. García-Heras, A. Jardines, A. Cervantes, M. Soler., "Predicting Air Traffic Flow Management hotspots due to weather using Convolutional Neural Networks", Engineering Applications of Artificial Intelligence. Volume 133, Part A, 2024, 108014, ISSN 0952-1976, https://doi.org/10.1016/j.engappai. 2024.108014
2023
Frattolillo F, Brunori D, Iocchi L. Scalable and Cooperative Deep Reinforcement Learning Approaches for Multi-UAV Systems: A Systematic Review. Drones. 2023; 7(4):236. https://doi.org/10.3390/drones7040236
2021
D. Brunori, S. Colonnese, F. Cuomo, G. Flore, L. Iocchi, "Delivering Resources for Augmented Reality by UAVs: a Reinforcement Learning Approach," Frontiers in Communications and Networks, Volume 2, 2021, https://www.frontiersin.org/journals/communications-and-networks/articles/10.3389/frcmn.2021.709265DOI=10.3389/frcmn.2021.709265ISSN=2673-530X
A. Jardines, M. Soler, A. Cervantes, et al., “Convection indicator for
pre-tactical air traffic flow management using neural networks,” Machine Learningwith Applications, vol. 5, p. 100 053, 2021​
A. Jardines, M. Soler, and J. García-Heras, “Estimating entry countsand atfm regulations during adverse weather conditions using machine learning,” Journal of Air Transport Management, vol. 95, p. 102 109, 2021
D. Brunori, S. Colonnese, F. Cuomo and L. Iocchi, "A Reinforcement Learning Environment for Multi-Service UAV-enabled Wireless Systems," 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), Kassel, Germany, 2021, pp. 251-256, doi: 10.1109/PerComWorkshops51409.2021.9431048.
2019
M. Ferro, D. Brunori, F. Magistri, L. Saiella, M. Selvaggio and G. A. Fontanelli, "A Portable da Vinci Simulator in Virtual Reality," 2019 Third IEEE International Conference on Robotic Computing (IRC), Naples, Italy, 2019, pp. 447-448, doi: 10.1109/IRC.2019.00093.