Archivio Istituzionale della RicercaCARDELLINI, MATTEO
CARDELLINI, MATTEO
Dipartimento di Automatica e Informatica
091351
A Planning-based Approach for In-Station Train Dispatching
2021 Cardellini, Matteo; Maratea, Marco; Vallati, Mauro; Boleto, Gianluca; Oneto, Luca
A Two-Phase ASP Encoding for Solving Rehabilitation Scheduling
2021 Cardellini, Matteo; De Nardi, Paolo; Dodaro, Carmine; Galatà, Giuseppe; Giardini, Anna; Maratea, Marco; Porro, Ivan
An ASP Framework for Efficient Urban Traffic Optimization
2022 Cardellini, M.
An Efficient Hybrid Planning Framework for In-Station Train Dispatching
2021 Cardellini, M.; Maratea, M.; Vallati, M.; Boleto, G.; Oneto, L.
Answer set programming in healthcare: Extended overview
2020 Alviano, Mario; Bertolucci, Riccardo; Cardellini, Matteo; Dodaro, Carmine; Galatà, Giuseppe; Muhammad, Khan; Maratea, Marco; Mochi, Marco; Morozan, Victoria; Porro, Ivan; Schouten, Marco
In-Station Train Dispatching: A PDDL+ Planning Approach
2021 Cardellini, Matteo; Maratea, Marco; Vallati, Mauro; Boleto, Gianluca; Oneto, Luca
In-Station Train Movements Prediction: from Shallow to Deep Multi Scale Models
2021 Boleto, G.; Oneto, L.; Cardellini, M.; Maratea, M.; Vallati, M.; Canepa, R.; Anguita, D.
| Citazione | Data di pubblicazione | Autori | File |
|---|---|---|---|
| A Planning-based Approach for In-Station Train Dispatching / Cardellini, Matteo; Maratea, Marco; Vallati, Mauro; Boleto, Gianluca; Oneto, Luca. - STAMPA. - 12:(2021), pp. 156-158. ((Intervento presentato al convegno 14th International Symposium on Combinatorial Search, SoCS 2021 tenutosi a Virtual Conference [Jinan, China] nel July 26-30, 2021. | 1-gen-2021 | Matteo Cardellini + | 18568-Article Text-22087-1-2-20210721.pdf |
| A Two-Phase ASP Encoding for Solving Rehabilitation Scheduling / Cardellini, Matteo; De Nardi, Paolo; Dodaro, Carmine; Galatà, Giuseppe; Giardini, Anna; Maratea, Marco; Porro, Ivan. - ELETTRONICO. - 12851:(2021), pp. 111-125. ((Intervento presentato al convegno International Joint Conference on Rules and Reasoning tenutosi a Online nel 2021/9/8 [10.1007/978-3-030-91167-6_8]. | 1-gen-2021 | Matteo Cardellini + | RuleML_RR2021.pdf; Cardellini2021_Chapter_ATwo-PhaseASPEncodingForSolvin.pdf |
| An ASP Framework for Efficient Urban Traffic Optimization / Cardellini, M.. - In: ELECTRONIC PROCEEDINGS IN THEORETICAL COMPUTER SCIENCE. - ISSN 2075-2180. - ELETTRONICO. - 364:(2022), pp. 217-227. ((Intervento presentato al convegno 18th Doctoral Consortium (DC) on Logic Programming tenutosi a Haifa, Israel nel 2nd August 2022 [10.4204/EPTCS.364.37]. | 1-gen-2022 | Cardellini M. | C7.pdf |
| An Efficient Hybrid Planning Framework for In-Station Train Dispatching / Cardellini, M.; Maratea, M.; Vallati, M.; Boleto, G.; Oneto, L.. - STAMPA. - (2021), pp. 168-182. ((Intervento presentato al convegno 21st International Conference on Computational Science, ICCS 2021 nel 2021 [10.1007/978-3-030-77961-0_15]. | 1-gen-2021 | Cardellini M. + | C3.pdf; 978-3-030-77961-0_15.pdf |
| Answer set programming in healthcare: Extended overview / Alviano, Mario; Bertolucci, Riccardo; Cardellini, Matteo; Dodaro, Carmine; Galatà, Giuseppe; Muhammad, Khan; Maratea, Marco; Mochi, Marco; Morozan, Victoria; Porro, Ivan; Schouten, Marco. - 2745:(2020). ((Intervento presentato al convegno Joint 8th Italian Workshop on Planning and Scheduling and the 27th International Workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion, IPS-RCRA 2020 tenutosi a Virtual event nel November 25-27, 2020. | 1-gen-2020 | Cardellini, Matteo + | C1.pdf |
| In-Station Train Dispatching: A PDDL+ Planning Approach / Cardellini, Matteo; Maratea, Marco; Vallati, Mauro; Boleto, Gianluca; Oneto, Luca. - STAMPA. - 31:(2021), pp. 450-458. ((Intervento presentato al convegno International Conference on Automated Planning and Scheduling, ICAPS 2021 tenutosi a Guangzhou, China (virtual) nel August 2-13, 2021. | 1-gen-2021 | Matteo Cardellini + | C2.pdf; 15991-Article Text-19484-1-2-20210517.pdf |
| In-Station Train Movements Prediction: from Shallow to Deep Multi Scale Models / Boleto, G.; Oneto, L.; Cardellini, M.; Maratea, M.; Vallati, M.; Canepa, R.; Anguita, D.. - STAMPA. - (2021), pp. 475-480. ((Intervento presentato al convegno 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2021 tenutosi a bel nel 2021 [10.14428/esann/2021.ES2021-29]. | 1-gen-2021 | Cardellini M. + | C5.pdf |