Publications

Pierre Andrews, Amine Benhalloum, Gerard Moreno-Torres Bertran, Matteo Bettini, Amar Budhiraja, Ricardo Silveira Cabral, Virginie Do, Romain Froger, Emilien Garreau, Jean-Baptiste Gaya, Hugo Laurençon, Maxime Lecanu, Kunal Malkan, Dheeraj Mekala, Pierre Ménard, Grégoire Mialon, Ulyana Piterbarg, Mikhail Plekhanov, Mathieu Rita, Andrey Rusakov, Thomas Scialom, Vladislav Vorotilov, Mengjue Wang, Ian Yu. ARE: Scaling Up Agent Environments and Evaluations. In Preprint, 2025.
Cite Code Dataset Docs arXiv Demo Meta AI Leaderboard Post
Matteo Bettini. Neural diversity in multi-agent learning. PhD Thesis, 2025.
PDF Cite University of Cambridge
Michael Amir*, Matteo Bettini*, Amanda Prorok. When Is Diversity Rewarded in Cooperative Multi-Agent Learning?. In Preprint, 2025.
PDF Cite arXiv
Matteo Bettini, Ryan Kortvelesy, Amanda Prorok. The impact of behavioral diversity in multi-agent reinforcement learning. In Preprint, 2025.
Cite Video Soccer trailer arXiv Code Ocean
Amanda Prorok, Matteo Bettini. Heterogeneous Teams. In Encyclopedia of Robotics, 2024.
Cite Springer link
Matteo Bettini, Ryan Kortvelesy, Amanda Prorok. Controlling Behavioral Diversity in Multi-Agent Reinforcement Learning. In International Conference on Machine Learning (ICML), 2024.
PDF Cite Code Website OpenReview arXiv Poster Talk
Jan Blumenkamp, Ajay Shankar, Matteo Bettini, Joshua Bird, Amanda Prorok. The Cambridge RoboMaster: An Agile Multi-Robot Research Platform. In Distributed Autonomous Robotic Systems (DARS), 2024.
PDF Cite Code Video Docs arXiv
Matteo Bettini, Amanda Prorok, Vincent Moens. BenchMARL: Benchmarking Multi-Agent Reinforcement Learning. In Journal of Machine Learning Research (JMLR), 2024.
PDF Cite Code Docs Wandb Benchmarks Talk Lecture arXiv Poster JMLR NeurIPS
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 Poster
Matteo Bettini, Ajay Shankar, Amanda Prorok. System Neural Diversity: Measuring Behavioral Heterogeneity in Multi-Agent Learning. In Journal of Machine Learning Research (JMLR), 2023.
PDF Cite Code JMLR 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 Poster
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 Talk Lecture arXiv
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
Matteo Bettini. Transport network design for vehicle routing: results on path addition and capacity reduction. MPhil Thesis, 2021.
PDF Cite Code Video