My Research Interest
My current research topics concern large-scale system coordination and machine learning algorithm in distributed systems. In my research group, we study a technique called Aggregate Computing, a top-down declarative approach to coordinate collective behaviour. Over the years, my colleagues developed novel tool-chain to use this new paradigm, such as ScaFi and Protelis.
My current trend consists in merging Aggregate Computing with Machine learning, gaining benefits of both worlds.
I am also the creator of ScaFi-Web, a web-based tool to use Aggregate Computing directly on the web.
Published articles
- Aguzzi, Audrito, Casadei, Damiani, Torta & Viroli (2023)
- Aguzzi, G., Audrito, G., Casadei, R., Damiani, F., Torta, G. & Viroli, M. (2023). A field-based computing approach to sensing-driven clustering in robot swarms. Swarm Intell., 17(1). 27–62. https://doi.org/10.1007/s11721-022-00215-y
- Aguzzi, Casadei, Pianini & Viroli (2022)
- Aguzzi, G., Casadei, R., Pianini, D. & Viroli, M. (2022). Dynamic decentralization domains for the internet of things. IEEE Internet Comput., 26(6). 16–23. https://doi.org/10.1109/MIC.2022.3216753
- Casadei, Viroli, Aguzzi & Pianini (2022)
- Casadei, R., Viroli, M., Aguzzi, G. & Pianini, D. (2022). ScaFi: A scala DSL and toolkit for aggregate programming. SoftwareX, 20. 101248. https://doi.org/10.1016/j.softx.2022.101248
- Aguzzi, Casadei & Viroli (2022)
- Aguzzi, G., Casadei, R. & Viroli, M. (2022). Addressing collective computations efficiency: Towards a platform-level reinforcement learning approach. IEEE. https://doi.org/10.1109/ACSOS55765.2022.00019
- Aguzzi, Casadei & Viroli (2022)
- Aguzzi, G., Casadei, R. & Viroli, M. (2022). Towards reinforcement learning-based aggregate computing. Springer. https://doi.org/10.1007/978-3-031-08143-9\_5
- Casadei, Pianini, Aguzzi, Audrito, Torta, Ottina, Damiani & Viroli (2022)
- Casadei, R., Pianini, D., Aguzzi, G., Audrito, G., Torta, G., Ottina, M., Damiani, F. & Viroli, M. (2022). Towards automated engineering for collective adaptive systems: Vision and research directions. IEEE. https://doi.org/10.1109/DASC/PiCom/CBDCom/Cy55231.2022.9927839
- Aguzzi, Casadei & Viroli (2022)
- Aguzzi, G., Casadei, R. & Viroli, M. (2022). Machine learning for aggregate computing: A research roadmap. IEEE. https://doi.org/10.1109/ICDCSW56584.2022.00032
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- Casadei, Aguzzi & Viroli (2021)
- Casadei, R., Aguzzi, G. & Viroli, M. (2021). A programming approach to collective autonomy. J. Sens. Actuator Networks, 10(2). 27. https://doi.org/10.3390/jsan10020027
- Aguzzi, Casadei, Pianini, Salvaneschi & Viroli (2021)
- Aguzzi, G., Casadei, R., Pianini, D., Salvaneschi, G. & Viroli, M. (2021). Towards pulverised architectures for collective adaptive systems through multi-tier programming. IEEE. https://doi.org/10.1109/ACSOS-C52956.2021.00033
- Aguzzi (2021)
- Aguzzi, G. (2021). Research directions for aggregate computing with machine learning. IEEE. https://doi.org/10.1109/ACSOS-C52956.2021.00078
- Aguzzi, Casadei, Maltoni, Pianini & Viroli (2021)
- Aguzzi, G., Casadei, R., Maltoni, N., Pianini, D. & Viroli, M. (2021). ScaFi-web: A web-based application for field-based coordination programming. Springer. https://doi.org/10.1007/978-3-030-78142-2\_18
- Delnevo, Aguzzi, Letizi, Luffarelli, Petreti & Mirri (2021)
- Delnevo, G., Aguzzi, G., Letizi, S., Luffarelli, M., Petreti, A. & Mirri, S. (2021). Encouraging users in waste sorting using deep neural networks and gamification. ACM. https://doi.org/10.1145/3462203.3477056