| Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning T Rashid*, M Samvelyan*, CS De Witt, G Farquhar, J Foerster, S Whiteson Journal of Machine Learning Research (JMLR), 2020 | 2481 | 2020 |
| The StarCraft Multi-Agent Challenge M Samvelyan*, T Rashid*, CS de Witt, G Farquhar, N Nardelli, ... AAMAS 2019, 2019 | 1047 | 2019 |
| MAVEN: Multi-Agent Variational Exploration A Mahajan, T Rashid, M Samvelyan, S Whiteson NeurIPS 2019, 2019 | 411 | 2019 |
| The Llama 3 Herd of Models A Dubey, A Jauhri, A Pandey, A Kadian, A Al-Dahle, A Letman, A Mathur, ... arXiv preprint arXiv:2407.21783, 2024 | 106 | 2024 |
| Evolving Curricula with Regret-Based Environment Design J Parker-Holder, M Jiang, M Dennis, M Samvelyan, J Foerster, ... ICML 2022, 2022 | 98 | 2022 |
| MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research M Samvelyan, R Kirk, V Kurin, J Parker-Holder, M Jiang, E Hambro, ... NeurIPS 2021, 2021 | 85 | 2021 |
| SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning B Ellis, J Cook, S Moalla, M Samvelyan, M Sun, A Mahajan, JN Foerster, ... NeurIPS 2023, 2022 | 58 | 2022 |
| Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning A Mahajan, M Samvelyan, L Mao, V Makoviychuk, A Garg, J Kossaifi, ... ICML 2021, 2021 | 39 | 2021 |
| JaxMARL: Multi-Agent RL Environments in JAX A Rutherford, B Ellis, M Gallici, J Cook, A Lupu, G Ingvarsson, T Willi, ... AAMAS 2024, 2023 | 25* | 2023 |
| MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning M Samvelyan, A Khan, MD Dennis, M Jiang, J Parker-Holder, JN Foerster, ... ICLR 2023, 2023 | 24 | 2023 |
| Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts M Samvelyan, SC Raparthy, A Lupu, E Hambro, AH Markosyan, M Bhatt, ... SeT LLMs @ ICLR 2024, 2024 | 19 | 2024 |
| Insights From the NeurIPS 2021 NetHack Challenge E Hambro, S Mohanty, D Babaev, M Byeon, D Chakraborty, ... NeurIPS 2021 Competitions and Demonstrations Track, 2022 | 18 | 2022 |
| Generalization in Cooperative Multi-Agent Systems A Mahajan, M Samvelyan, T Gupta, B Ellis, M Sun, T Rocktäschel, ... arXiv preprint arXiv:2202.00104, 2022 | 18 | 2022 |
| Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning M Matthews, M Beukman, B Ellis, M Samvelyan, M Jackson, S Coward, ... ICML 2024 (Spotlight), 2024 | 10 | 2024 |
| Reinforcement Learning in Factored Action Spaces Using Tensor Decompositions A Mahajan, M Samvelyan, L Mao, V Makoviychuk, A Garg, J Kossaifi, ... 2nd Workshop on Quantum Tensor Networks in Machine Learning @ NeurIPS 2021, 2021 | 10 | 2021 |
| GriddlyJS: A Web IDE for Reinforcement Learning C Bamford, M Jiang, M Samvelyan, T Rocktäschel NeurIPS 2022, 2022 | 7 | 2022 |
| Hierarchical Kickstarting for Skill Transfer in Reinforcement Learning M Matthews, M Samvelyan, J Parker-Holder, E Grefenstette, ... CoLLAs 2022, 2022 | 4 | 2022 |
| SkillHack: A Benchmark for Skill Transfer in Open-Ended Reinforcement Learning M Matthews, M Samvelyan, J Parker-Holder, E Grefenstette, ... Workshop on Agent Learning in Open-Endedness @ ICLR 2022, 2022 | 3 | 2022 |
| Mix-ME: Quality-Diversity for Multi-Agent Learning G Ingvarsson, M Samvelyan, B Lim, M Flageat, A Cully, T Rocktäschel ALOE @ NeurIPS 2023, 2023 | 2 | 2023 |
| Pax: Multi-Agent Learning in Jax T Willi, A Khan, N Kwan, M Samvelyan, C Lu, J Foerster GitHub Repository, 2023 | 2 | 2023 |
Jakob FoersterAssociate Professor, University of Oxford確認したメール アドレス: eng.ox.ac.uk
