Optimal Planning and Routing in Medium Voltage PowerLine Communications Networks S Canale, A Di Giorgio, A Lanna, A Mercurio, M Panfili, A Pietrabissa Smart Grid, IEEE Transactions on, 1-9, 2012 | 45 | 2012 |
A resource allocation algorithm of multi-cloud resources based on markov decision process G Oddi, M Panfili, A Pietrabissa, L Zuccaro, V Suraci 2013 IEEE 5th international conference on cloud computing technology and …, 2013 | 44 | 2013 |
An approximate dynamic programming approach to resource management in multi-cloud scenarios A Pietrabissa, FD Priscoli, A Di Giorgio, A Giuseppi, M Panfili, V Suraci International Journal of Control 90 (3), 492-503, 2017 | 41 | 2017 |
A game-theoretical approach to cyber-security of critical infrastructures based on multi-agent reinforcement learning M Panfili, A Giuseppi, A Fiaschetti, HB Al-Jibreen, A Pietrabissa, ... 2018 26th Mediterranean Conference on Control and Automation (MED), 460-465, 2018 | 34 | 2018 |
A future internet oriented user centric extended intelligent transportation system S Canale, A Di Giorgio, F Lisi, M Panfili, LR Celsi, V Suraci, FD Priscoli 2016 24th Mediterranean Conference on Control and Automation (MED), 1133-1139, 2016 | 26 | 2016 |
Resilient planning of powerline communications networks over medium voltage distribution grids S Canale, FD Priscoli, A Di Giorgio, A Lanna, A Mercurio, M Panfili, ... 2012 20th Mediterranean Conference on Control & Automation (MED), 710-715, 2012 | 26 | 2012 |
A multi-agent reinforcement learning based approach to quality of experience control in future internet networks B Stefano, DP Francesco, GG Claudio, M Salvatore, P Martina, P Antonio, ... 2015 34th Chinese Control Conference (CCC), 6495-6500, 2015 | 16 | 2015 |
A Q-Learning based approach to Quality of Experience control in cognitive Future Internet networks LR Celsi, S Battilotti, F Cimorelli, CG Giorgi, S Monaco, M Panfili, V Suraci, ... 2015 23rd Mediterranean Conference on Control and Automation (MED), 1045-1052, 2015 | 15 | 2015 |
Resource management in multi-cloud scenarios via reinforcement learning P Antonio, B Stefano, F Francisco, G Alessandro, O Guido, P Martina, ... 2015 34th Chinese Control Conference (CCC), 9084-9089, 2015 | 12 | 2015 |
Approaches for Future Internet Architecture Design and Quality of Experience (QoE) Control S Battilotti, F DELLI PRISCOLI, C GORI GIORGI, A Pietrabissa, S Monaco, ... WSEAS Transactions on Communications 14, 62-73, 2015 | 8 | 2015 |
A lexicographic approach to constrained MDP admission control M Panfili, A Pietrabissa, G Oddi, V Suraci International Journal of Control 89 (2), 235-247, 2016 | 5 | 2016 |
Attack-surface metrics, osstmm and common criteria based approach to “composable security” in complex systems A Fiaschetti, A Lanna, M Panfili, S Mignanti, A Pietrabissa, ... WSEAS Transactions on Systems 14, 187-202, 2015 | 5 | 2015 |
CADUCEO: A Platform to Support Federated Healthcare Facilities through Artificial Intelligence D Menegatti, A Giuseppi, F Delli Priscoli, A Pietrabissa, A Di Giorgio, ... Healthcare 11 (15), 2199, 2023 | 4 | 2023 |
Optimal control of industrial assembly lines F Liberati, A Tortorelli, C Mazquiaran, M Imran, M Panfili 2020 7th International Conference on Control, Decision and Information …, 2020 | 4 | 2020 |
Control architecture to provide E2E security in interconnected systems: the (new) SHIELD approach A Fiaschetti, A Morgagni, A Lanna, M Panfili, S Mignanti, R Cusani, ... Advances in Information Science and Applications 2, 359-365, 2014 | 3 | 2014 |
Overall system architecture and interfaces D Christofi, GD PTL, G Gardikis, EM Bourdena, E Pallis, PP LUH, ... | 1 | 2014 |
The SHIELD Approach A Fiaschetti, P Azzoni, J Noll, R Uribeetxeberria, A Pietrabissa, FD Priscoli, ... Measurable and Composable Security, Privacy, and Dependability for …, 2017 | | 2017 |
An Approach Based on Reinforcement Learning for Quality of Experience (QoE) Control S Battilotti, F Cimorelli, F DELLI PRISCOLI, C GORI GIORGI, S Monaco, ... RECENT ADVANCES IN COMPUTER ENGINEERING 2, 481-486, 2014 | | 2014 |
An Approach Based on Reinforcement Learning for Quality of Experience (QoE) Control F Cimorelli, M Panfili, S Battilotti, FD Priscoli, CG Giorgi, S Monaco | | |