VIZZARI GIUSEPPE

Guidotti, S., Donabauer, G., Taibi, D., Vizzari, G., Kruschwitz, U., Ognibene, D. (2026). Introducing a Novel Framework for Recognizing Social Media Recommenders Under Absent Recommendations and a First Graph Neural Network-Based Implementation. Intervento presentato a: 7th International Workshop on Agents for Societal Impact (ASI). In conjunction with the 25th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Paphos, Cyprus. Detail

Lin, X., Vizzari, G., Feliciani, C., Yanagisawa, D., Nishinari, K. (2026). Explaining COVID-19 Tokyo metro station-level ridership disruption and recovery: pre-pandemic demand, built environment and centrality. TRANSPORTATION RESEARCH. PART D, TRANSPORT AND ENVIRONMENT, 161 [10.1016/j.trd.2026.105619]. Detail

Vizzari, G., Briola, D. (2026). Simulation and Agent-Based Simulation at WOA: 25 of Years of Simulation-Related Contributions, and an Outlook of What Awaits Us. In V. Mascardi, A. Omicini (a cura di), The Agents Journey - Twenty-Five Years of Multi-agent Systems (pp. 260-283). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-032-22940-3_10]. Detail

Guidotti, S., Donabauer, G., Taibi, D., Vizzari, G., Kruschwitz, U., Ognibene, D. (2026). Toward Recognizing Social Media Recommenders under Absent Recommendations: A Graph Neural Network-based Approach. In AAMAS '26: Proceedings of the 25th International Conference on Autonomous Agents and Multiagent Systems (pp.3658-3660). Association for Computing Machinery, Inc [10.65109/ymxq7472]. Detail

Vizzari, G., Falbo, A., Tenderini, R., Briola, D. (2026). RL-Godot pedestrian simulation: curriculum-based reinforcement learning for pedestrian simulation. In Pedestrian and Evacuation Dynamics 2025 (pp.323-329). Ceske Vysoke Uceni Technicke,Czech Technical University in Prague [10.14311/app.2026.57.0323]. Detail