POPGym: Benchmarking Partially Observable Reinforcement Learning S Morad, R Kortvelesy, M Bettini, S Liwicki, A Prorok International Conference on Learning Representations, 2023 | 23 | 2023 |
Heterogeneous Multi-Robot Reinforcement Learning M Bettini, A Shankar, A Prorok Autonomous Agents and Multiagent Systems, 1485–1494, 2023 | 22 | 2023 |
VMAS: A Vectorized Multi-Agent Simulator for Collective Robot Learning M Bettini, R Kortvelesy, J Blumenkamp, A Prorok Distributed Autonomous Robotic Systems, 2022 | 13 | 2022 |
TorchRL: A data-driven decision-making library for PyTorch A Bou, M Bettini, S Dittert, V Kumar, S Sodhani, X Yang, G De Fabritiis, ... ICLR 2024, 2023 | 8 | 2023 |
BenchMARL: Benchmarking Multi-Agent Reinforcement Learning M Bettini, A Prorok, V Moens arXiv preprint arXiv:2312.01472, 2023 | 2 | 2023 |
System Neural Diversity: Measuring Behavioral Heterogeneity in Multi-Agent Learning M Bettini, A Shankar, A Prorok arXiv preprint arXiv:2305.02128, 2023 | 2 | 2023 |
On the properties of path additions for traffic routing M Bettini, A Prorok arXiv preprint arXiv:2207.04505, 2022 | | 2022 |
Evaluating Benefits of Heterogeneity in Constrained Multi-Agent Learning A Shaw, M Bettini | | |