Outcomes

Here, we present the progress and achievements of our research initiative, focused on enhancing human-machine collaboration. Over the course of the project, we have delved into various facets of AI and human interaction, contributing significantly to both academic research and practical applications.

Our team's efforts are reflected in a range of outputs, including scholarly articles, workshops, and collaborations with leading institutions and industry partners. As the project evolves, we will continue to update this page with our latest findings and milestones. 

Scientific Outcomes

Year 2023

• Nicolo' Brandizzi, Carolina Centeio Jorge, Roberto Cipollone, Francesco Frattolillo, Luca Iocchi, and Anna-Sophie Ulfert-Blank. 2023. MULTITTRUST: 2nd Workshop on Multidisciplinary Perspectives on Human-AI Team Trust. In Proceedings of the 11th International Conference on Human-Agent Interaction (HAI '23). Association for Computing Machinery, New York, NY, USA, 496–497. https://doi.org/10.1145/3623809.3623978

• N. Brandizzi, "Towards More Human-like AI Communication: A Review of Emergent Communication Research," in IEEE Access, doi: 10.1109/ACCESS.2023.3339656.

• Frattolillo, F., Brandizzi, N., Cipollone, R., & Iocchi, L. (2024). Towards computational models for reinforcement learning in human-AI teams. In Proceedings of the 2nd International Workshop on Multidisciplinary Perspectives on Human-AI Team Trust. https://ceur-ws.org/Vol-3634/paper9.pdf

Year 2024

• Edited and published a volume in the CEUR Workshop Proceedings https://ceur-ws.org/Vol-3634/

• Simone Di Rienzo, Francesco Frattolillo, Roberto Cipollone, Andrea Fanti, Nicolo’ Brandizzi and Luca Iocchi. Developing Targeted Communication through a Trust Factor in Multi-Agent Reinforcement Learning. MultiTTrust 3.0 Workshop. HHAI 2024 Conference. https://ceur-ws.org/Vol-3825/extendedAbstract5-2.pdf 

• Giuseppe Contino, Francesco Frattolillo, Roberto Cipollone, Andrea Fanti, Nicolo’ Brandizzi and Luca Iocchi. Modeling a Trust Factor in Composite Tasks for Multi-Agent Reinforcement Learning. In Proc. of HAI 2024. https://dl.acm.org/doi/10.1145/3687272.3688325 

Networking Outcomes

Year 2023

• 2nd Edition of the MultiTTrust Workshop at Human-Agent Interaction (HAI '23)

• Collaboration with Future Artificial Intelligence Research (FAIR).

Year 2024

• 3rd Edition of the MultiTTrust Workshop at Hybrid Human Artificial Intelligence (HHAI '24)

• Special Issue on Multidisciplinary Perspectives on Human-AI Team Trust  at Interaction Studies Journal