| Smacv2: An improved benchmark for cooperative multi-agent reinforcement learning B Ellis, J Cook, S Moalla, M Samvelyan, M Sun, A Mahajan, J Foerster, ... Advances in Neural Information Processing Systems 36, 2024 | 63 | 2024 |
| Lift: Reinforcement learning in computer systems by learning from demonstrations M Schaarschmidt, A Kuhnle, B Ellis, K Fricke, F Gessert, E Yoneki arXiv preprint arXiv:1808.07903, 2018 | 45 | 2018 |
| Jaxmarl: Multi-agent rl environments in jax A Rutherford*, B Ellis*, M Gallici*, J Cook, A Lupu, G Ingvarsson, T Willi, ... arXiv preprint arXiv:2311.10090, 2023 | 27* | 2023 |
| Generalization in cooperative multi-agent systems A Mahajan, M Samvelyan, T Gupta, B Ellis, M Sun, T Rocktäschel, ... arXiv preprint arXiv:2202.00104, 2022 | 19 | 2022 |
| Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning M Matthews, M Beukman, B Ellis, M Samvelyan, M Jackson, S Coward, ... arXiv preprint arXiv:2402.16801, 2024 | 11 | 2024 |
| Policy-guided diffusion MT Jackson, MT Matthews, C Lu, B Ellis, S Whiteson, J Foerster arXiv preprint arXiv:2404.06356, 2024 | 5 | 2024 |
| Trust-region-free policy optimization for stochastic policies M Sun, B Ellis, A Mahajan, S Devlin, K Hofmann, S Whiteson arXiv preprint arXiv:2302.07985, 2023 | 3 | 2023 |
| Simplifying Deep Temporal Difference Learning M Gallici, M Fellows, B Ellis, B Pou, I Masmitja, JN Foerster, M Martin arXiv preprint arXiv:2407.04811, 2024 | 2 | 2024 |
| Adaptive stream processing with deep reinforcement learning B Ellis Technical Report, 2018 | 1 | 2018 |
| Investigating Ratio Clipping in Multi-agent Reinforcement Learning B Ellis, M Sun, S Whiteson | | |
