Publications

Amanda Prorok, Matteo Bettini. Heterogeneous Teams. In Encyclopedia of Robotics, 2024.
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Matteo Bettini, Ryan Kortvelesy, Amanda Prorok. Controlling Behavioral Diversity in Multi-Agent Reinforcement Learning. In International Conference on Machine Learning (ICML), 2024.
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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.
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Matteo Bettini, Amanda Prorok, Vincent Moens. BenchMARL: Benchmarking Multi-Agent Reinforcement Learning. In Journal of Machine Learning Research (JMLR), 2024.
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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.
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Matteo Bettini, Ajay Shankar, Amanda Prorok. System Neural Diversity: Measuring Behavioral Heterogeneity in Multi-Agent Learning. In Preprint, 2023.
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Matteo Bettini, Ajay Shankar, Amanda Prorok. Heterogeneous Multi-Robot Reinforcement Learning. In Autonomous Agents and Multiagent Systems (AAMAS), 2023.
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Steven Morad, Ryan Kortvelesy, Matteo Bettini, Stephan Liwicki, Amanda Prorok. POPGym: Benchmarking Partially Observable Reinforcement Learning. In International Conference on Learning Representations (ICLR), 2023.
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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.
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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.
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Matteo Bettini. Transport network design for vehicle routing: results on path addition and capacity reduction. MPhil Thesis, 2021.
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