Publications

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Journal Articles

Digital Twin Aggregates for adaptive MLOps retraining policies in healthcare

Published in Future Generation Computer Systems, Volume 185, Article 108674, 2026

Recommended citation: Davide Domini, Leonardo Micelli, Samuele Burattini, Sara Montagna (2026). "Digital Twin Aggregates for adaptive MLOps retraining policies in healthcare" Future Generation Computer Systems, Volume 185, Article 108539, Article 108674.
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ProFed: A Benchmark for Proximity-Based Non-IID Federated Learning

Published in Journal of Open Research Software, Volume 14, 2026

Recommended citation: Davide Domini, Christian Otte Ingemann, Gianluca Aguzzi, Lukas Esterle, Mirko Viroli (2026). "ProFed: A Benchmark for Proximity-Based Non-IID Federated Learning." Journal of Open Research Software, Volume 14, pp. 1–13.
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Heterogeneous GNN for collective-task offloading in cloud-edge via deep Q-learning

Published in Future Generation Computer Systems, Volume 183, Article 108539, 2026

Recommended citation: Nicolas Farabegoli, Davide Domini, Gianluca Aguzzi, Mirko Viroli (2026). "Heterogeneous GNN for collective-task offloading in cloud-edge via deep Q-learning." Future Generation Computer Systems, Volume 183, Article 108539, Article 108539.
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FBFL: A Field-Based Coordination Approach for Data Heterogeneity in Federated Learning

Published in Logical Methods in Computer Science, Volume 22, Issue 1, 2026

Recommended citation: Davide Domini, Gianluca Aguzzi, Lukas Esterle, Mirko Viroli (2026). "FBFL: A Field-Based Coordination Approach for Data Heterogeneity in Federated Learning." Logical Methods in Computer Science, Volume 22, Issue 1, pp. 1–30.
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Decentralized proximity-aware clustering for collective self-federated learning

Published in Internet of Things, Volume 35, Article 101841, 2026

Recommended citation: Davide Domini, Nicolas Farabegoli, Gianluca Aguzzi, Mirko Viroli, Lukas Esterle (2026). "Decentralized proximity-aware clustering for collective self-federated learning." Internet of Things, Volume 35, Article 101841, Article 101841.
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Scaling Swarm Coordination with GNNs—How Far Can We Go?

Published in AI, Volume 6, Issue 11, Article 282, 2025

Recommended citation: Gianluca Aguzzi, Davide Domini, Federico Venturini, and Mirko Viroli (2025). "Scaling Swarm Coordination with GNNs—How Far Can We Go?" AI, 6(11), Article 282.

ScaRLib: Towards a hybrid toolchain for aggregate computing and many-agent reinforcement learning

Published in Science of Computer Programming, Volume 238, Article 103176, 2024

Recommended citation: Davide Domini, Filippo Cavallari, Gianluca Aguzzi, Mirko Viroli (2024). "ScaRLib: Towards a hybrid toolchain for aggregate computing and many-agent reinforcement learning." Science of Computer Programming, Volume 238, Article 103176, Article 103176.
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Conference Papers

HarmoniKt: a Unifying Middleware for Heterogeneous Robot Fleets

Published in 2026 IEEE 23rd Consumer Communications & Networking Conference (CCNC), 2026

Recommended citation: Manuel Andruccioli, Angela Cortecchia, Davide Domini, Nicolas Farabegoli, Giovanni Delnevo, Danilo Pianini, Riccardo Venanzi, Mirko Viroli (2026). "HarmoniKt: a Unifying Middleware for Heterogeneous Robot Fleets." 2026 IEEE 23rd Consumer Communications & Networking Conference (CCNC), pp. 1–6.
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Phyelds: A Pythonic Framework for Aggregate Computing

Published in International Conference on Coordination Models and Languages, 2026

Recommended citation: Gianluca Aguzzi, Davide Domini, Nicolas Farabegoli, Mirko Viroli (2026). "Phyelds: A Pythonic Framework for Aggregate Computing." International Conference on Coordination Models and Languages, pp. 174–191.
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A Demonstrator for Self-organizing Robot Teams

Published in International Conference on Coordination Models and Languages, 2025

Recommended citation: Gianluca Aguzzi, Lorenzo Bacchini, Martina Baiardi, Roberto Casadei, Angela Cortecchia, Davide Domini, Nicolas Farabegoli, Danilo Pianini, Mirko Viroli (2025). "A Demonstrator for Self-organizing Robot Teams." International Conference on Coordination Models and Languages, pp. 230–244.
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Sparse Self-Federated Learning for Energy Efficient Cooperative Intelligence in Society 5.0

Published in International Joint Conference on Neural Networks (IJCNN 2025), 2025

Recommended citation: Davide Domini, Laura Erhan, Gianluca Aguzzi, Lucia Cavallaro, Amirhossein Douzandeh Zenoozi, Antonio Liotta, Mirko Viroli (2025). "Sparse Self-Federated Learning for Energy Efficient Cooperative Intelligence in Society 5.0." International Joint Conference on Neural Networks (IJCNN 2025), pp. 1–8.
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Neighbor-Based Decentralized Training Strategies for Multi-Agent Reinforcement Learning

Published in The 40th ACM/SIGAPP Symposium on Applied Computing (SAC 2025), 2025

Recommended citation: Nicolò Malucelli, Davide Domini, Gianluca Aguzzi, Mirko Viroli (2025). "Neighbor-Based Decentralized Training Strategies for Multi-Agent Reinforcement Learning." The 40th ACM/SIGAPP Symposium on Applied Computing (SAC 2025), pp. 1250–1257.
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Proximity-based Self-Federated Learning

Published in IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS 2024), 2024

Recommended citation: Davide Domini, Gianluca Aguzzi, Nicolas Farabegoli, Mirko Viroli, Lukas Esterle (2024). "Proximity-based Self-Federated Learning." IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS 2024), pp. 139–144.
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Field-Based Coordination for Federated Learning

Published in International Conference on Coordination Models and Languages, 2024

Recommended citation: Davide Domini, Gianluca Aguzzi, Lukas Esterle, Mirko Viroli (2024). "Field-Based Coordination for Federated Learning." International Conference on Coordination Models and Languages, pp. 56–74.
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A Reusable Simulation Pipeline for Many-Agent Reinforcement Learning

Published in IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications (DS-RT 2024), 2024

Recommended citation: Davide Domini, Gianluca Aguzzi, Danilo Pianini, Mirko Viroli (2024). "A Reusable Simulation Pipeline for Many-Agent Reinforcement Learning." IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications (DS-RT 2024), pp. 83–90.
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ScaRLib: A Framework for Cooperative Many Agent Deep Reinforcement Learning in Scala

Published in International Conference on Coordination Models and Languages3, 2023

Recommended citation: Davide Domini, Filippo Cavallari, Gianluca Aguzzi, Mirko Viroli (2023). "ScaRLib: A Framework for Cooperative Many Agent Deep Reinforcement Learning in Scala." International Conference on Coordination Models and Languages, pp. 52–70.
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Workshop Papers

Towards Self-Adaptive Cooperative Learning in Collective Systems

Published in ACSOS-C 2024, 2024

Recommended citation: Davide Domini (2024). "Towards Self-Adaptive Cooperative Learning in Collective Systems." ACSOS-C 2024, pp. 158–160.
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Towards Intelligent Pulverized Systems: a Modern Approach for Edge-Cloud Services

Published in WOA 2024, the 25th Workshop From Objects to Agents, 2024

Recommended citation: Davide Domini, Nicolas Farabegoli, Gianluca Aguzzi, Mirko Viroli (2024). "Towards Intelligent Pulverized Systems: a Modern Approach for Edge-Cloud Services." WOA 2024, the 25th Workshop From Objects to Agents, pp. 233–251.
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Preprint Papers

Discovering Collaboration from Novelty: Random Network Distillation for Clustered Federated Learning

Published in arXiv preprint, 2026

Recommended citation: Davide Domini, Gianluca Aguzzi, Ivana Dusparic, Danilo Pianini, Mirko Viroli (2026). "Discovering Collaboration from Novelty: Random Network Distillation for Clustered Federated Learning." arXiv preprint.
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Flexible Distributed Particle Filtering for the Internet of Things via Aggregate Computing

Published in arXiv preprint, 2026

Recommended citation: Angela Cortecchia, Davide Domini, Giovanni Ciatto, Roberto Casadei, Danilo Pianini, Mirko Viroli (2026). "Flexible Distributed Particle Filtering for the Internet of Things via Aggregate Computing." arXiv preprint.
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C2FL: Clustered Continual Federated Learning under Spatial and Temporal Drift

Published in arXiv preprint, 2026

Recommended citation: Davide Domini, Gianluca Aguzzi, Lorenzo Pellegrini, Mirko Viroli, Lukas Esterle (2026). "C2FL: Clustered Continual Federated Learning under Spatial and Temporal Drift." arXiv preprint.
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