ScaRLib: A Framework for Cooperative Many Agent Deep Reinforcement Learning in Scala. - Davide Domini; Filippo Cavallari; Gianluca Aguzzi; Mirko Viroli (COORDINATION, 2023)

Towards Self-Adaptive Cooperative Learning in Collective Systems. - Davide Domini (ACSOS-C, 2024)

Proximity-based Self-Federated Learning. - Davide Domini; Gianluca Aguzzi; Nicolas Farabegoli; Mirko Viroli; Lukas Esterle (ACSOS, 2024)

Field-Based Coordination for Federated Learning. - Davide Domini; Gianluca Aguzzi; Lukas Esterle; Mirko Viroli (COORDINATION, 2024)

A Reusable Simulation Pipeline for Many-Agent Reinforcement Learning. - Davide Domini; Gianluca Aguzzi; Danilo Pianini; Mirko Viroli (DS-RT, 2024)

Towards Intelligent Pulverized Systems: a Modern Approach for Edge-Cloud Services. - Davide Domini; Nicolas Farabegoli; Gianluca Aguzzi; Mirko Viroli (WOA, 2024)

ScaRLib: Towards a hybrid toolchain for aggregate computing and many-agent reinforcement learning. - Davide Domini; Filippo Cavallari; Gianluca Aguzzi; Mirko Viroli (Sci. Comput. Program., 2024)

A Demonstrator for Self-organizing Robot Teams. - Gianluca Aguzzi; Lorenzo Bacchini; Martina Baiardi; Roberto Casadei; Angela Cortecchia; Davide Domini; Nicolas Farabegoli; Danilo Pianini; Mirko Viroli (COORDINATION, 2025)

Neighbor-Based Decentralized Training Strategies for Multi-Agent Reinforcement Learning. - Nicolò Malucelli; Davide Domini; Gianluca Aguzzi; Mirko Viroli (SAC, 2025)

FBFL: A Field-Based Coordination Approach for Data Heterogeneity in Federated Learning. - Davide Domini; Gianluca Aguzzi; Lukas Esterle; Mirko Viroli (CoRR, 2025)

ProFed: a Benchmark for Proximity-based non-IID Federated Learning. - Davide Domini; Gianluca Aguzzi; Mirko Viroli (CoRR, 2025)

Sparse Self-Federated Learning for Energy Efficient Cooperative Intelligence in Society 5.0. - Davide Domini; Laura Erhan; Gianluca Aguzzi; Lucia Cavallaro; Amirhossein Douzandeh Zenoozi; Antonio Liotta; Mirko Viroli (CoRR, 2025)