Publications

Throughout the years this research groups contributed multiple times to the Reinforcement Learning community, following are the more relevant publications

2024

• “A Fairness-Oriented Reinforcement Learning Approach for the Operation and Control of Shared Micromobility Services”, L.V. Piron, M. Cederle, M. Ceccon, F. Chiariotti, A. Fabris, M. Fabris, G.A. Susto, to the 63rd Conference on Decision and Control, Dec. 16-19, 2024, Milan, Italy. arXiv:2403.15780v1 [eess.SY]
• Sinigaglia, A., Turcato, N., Libera, A. D., Carli, R., & Susto, G. A. (2024). Exploiting Estimation Bias in Deep Double Q-Learning for Actor-Critic Methods.
• Wiebe, F., Turcato, N., Dalla Libera, A., Zhang, C., Vincent, T., Vyas, S., ... & Kumar, S. (2024). Reinforcement learning for athletic intelligence: Lessons from the 1st “ai olympics with realaigym” competition,”. In Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, IJCAI-24, K. Larson, Ed. International Joint Conferences on Artificial Intelligence Organization (Vol. 8, pp. 8833-8837).
• Turcato, N., Libera, A. D., Giacomuzzo, G., Carli, R., & Romeres, D. (2024). Learning control of underactuated double pendulum with Model-Based Reinforcement Learning. arXiv preprint arXiv:2409.05811.
• Calì, M., Sinigaglia, A., Turcato, N., Carli, R., & Susto, G. A. (2024). AI Olympics challenge with Evolutionary Soft Actor Critic. arXiv preprint arXiv:2409.01104.

2023

• N. Turcato, A. D. Libera, G. Giacomuzzo and R. Carli, "Teaching a Robot to Toss Arbitrary Objects with Model-Based Reinforcement Learning," 2023 9th International Conference on Control, Decision and Information Technologies (CoDIT), Rome, Italy, 2023, pp. 1126-1131, doi: 10.1109/CoDIT58514.2023.10284290.
• Marcato, D., Bellan, L., Bortolato, D., Comunian, M., Galatà, A., Gelain, F., ... & Susto, G. A. (2023). Demonstration of Beam Emittance Optimization using Reinforcement Learning. In Proceedings of the 14th International Particle Accelerator Conference.

2022

• Calvi, G., Manzoni, E., Rampazzo, M. (2022). Reinforcement Q-learning for Closed-loop Hypnosis Depth Control in Anesthesia. In 2022 30th Mediterranean Conference on Control and Automation (MED) (pp. 164-169). IEEE.

2020

• Maggipinto, M., Susto, G. A., & Chaudhari, P. Proximal deterministic policy gradient. In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 5438-5444). IEEE.

2017

• Beghi, A., Rampazzo, M., Zorzi, S. (2017). Reinforcement learning control of transcritical carbon dioxide supermarket refrigeration systems. IFAC-PapersOnLine, 50(1), 13754-13759.