Publications

Albert Bou, Matteo Bettini, Sebastian Dittert, Vikash Kumar, Shagun Sodhani, Xiaomeng Yang, Gianni De Fabritiis, Vincent Moens. TorchRL: A data-driven decision-making library for PyTorch. In International Conference on Learning Representations (ICLR) - Spotlight (top 5%), 2024.
PDF Cite Code Documentation arXiv OpenReview
Matteo Bettini, Amanda Prorok, Vincent Moens. BenchMARL: Benchmarking Multi-Agent Reinforcement Learning. In Preprint, 2023.
PDF Cite Code Docs Wandb Benchmarks Talk arXiv
Matteo Bettini, Ajay Shankar, Amanda Prorok. System Neural Diversity: Measuring Behavioral Heterogeneity in Multi-Agent Learning. In Preprint, 2023.
PDF Cite Code arXiv
Matteo Bettini, Ajay Shankar, Amanda Prorok. Heterogeneous Multi-Robot Reinforcement Learning. In Autonomous Agents and Multiagent Systems (AAMAS), 2023.
PDF Cite Code Video arXiv Talk Poster
Steven Morad, Ryan Kortvelesy, Matteo Bettini, Stephan Liwicki, Amanda Prorok. POPGym: Benchmarking Partially Observable Reinforcement Learning. In International Conference on Learning Representations (ICLR), 2023.
PDF Cite Code arXiv OpenReview
Matteo Bettini, Ryan Kortvelesy, Jan Blumenkamp, Amanda Prorok. VMAS: A Vectorized Multi-Agent Simulator for Collective Robot Learning. In Distributed Autonomous Robotic Systems (DARS), 2022.
PDF Cite Code Video arXiv Talk
Matteo Bettini, Amanda Prorok. On the Properties of Path Additions for Traffic Routing. In IEEE International Conference on Intelligent Transportation Systems (ITSC) Workshop on Co-Design and Coordination of Future Mobility Systems, 2022.
PDF Cite Code arXiv