Human-level control through deep reinforcement learning V Mnih, K Kavukcuoglu, D Silver, AA Rusu, J Veness, MG Bellemare, ... nature 518 (7540), 529-533, 2015 | 32855 | 2015 |
Accurate structure prediction of biomolecular interactions with AlphaFold 3 J Abramson, J Adler, J Dunger, R Evans, T Green, A Pritzel, ... Nature, 1-3, 2024 | 1504 | 2024 |
Human-level performance in 3D multiplayer games with population-based reinforcement learning M Jaderberg, WM Czarnecki, I Dunning, L Marris, G Lever, AG Castaneda, ... Science 364 (6443), 859-865, 2019 | 1018 | 2019 |
Vector-based navigation using grid-like representations in artificial agents A Banino, C Barry, B Uria, C Blundell, T Lillicrap, P Mirowski, A Pritzel, ... Nature 557 (7705), 429-433, 2018 | 769 | 2018 |
Massively parallel methods for deep reinforcement learning A Nair, P Srinivasan, S Blackwell, C Alcicek, R Fearon, A De Maria, ... arXiv preprint arXiv:1507.04296, 2015 | 654 | 2015 |
Deepmind lab C Beattie, JZ Leibo, D Teplyashin, T Ward, M Wainwright, H Küttler, ... arXiv preprint arXiv:1612.03801, 2016 | 627 | 2016 |
A multi-agent reinforcement learning model of common-pool resource appropriation J Perolat, JZ Leibo, V Zambaldi, C Beattie, K Tuyls, T Graepel Advances in neural information processing systems 30, 2017 | 233 | 2017 |
Scalable evaluation of multi-agent reinforcement learning with melting pot JZ Leibo, EA Dueñez-Guzman, A Vezhnevets, JP Agapiou, P Sunehag, ... International conference on machine learning, 6187-6199, 2021 | 97 | 2021 |
Psychlab: a psychology laboratory for deep reinforcement learning agents JZ Leibo, CM d'Autume, D Zoran, D Amos, C Beattie, K Anderson, ... arXiv preprint arXiv:1801.08116, 2018 | 59 | 2018 |
Inferring a continuous distribution of atom coordinates from cryo-EM images using VAEs D Rosenbaum, M Garnelo, M Zielinski, C Beattie, E Clancy, A Huber, ... arXiv preprint arXiv:2106.14108, 2021 | 49 | 2021 |
Quantifying the effects of environment and population diversity in multi-agent reinforcement learning KR McKee, JZ Leibo, C Beattie, R Everett Autonomous Agents and Multi-Agent Systems 36 (1), 21, 2022 | 34 | 2022 |
Deepmind lab2d C Beattie, T Köppe, EA Duéñez-Guzmán, JZ Leibo arXiv preprint arXiv:2011.07027, 2020 | 22 | 2020 |
Uncovering surprising behaviors in reinforcement learning via worst-case analysis A Ruderman, R Everett, B Sikder, H Soyer, J Uesato, A Kumar, C Beattie, ... | 13 | 2019 |
Deep reinforcement learning models the emergent dynamics of human cooperation KR McKee, E Hughes, TO Zhu, MJ Chadwick, R Koster, AG Castaneda, ... arXiv preprint arXiv:2103.04982, 386-418, 2021 | 12 | 2021 |
Quantifying environment and population diversity in multi-agent reinforcement learning KR McKee, JZ Leibo, C Beattie, R Everett arXiv preprint arXiv:2102.08370, 2021 | 11 | 2021 |
A multi-agent reinforcement learning model of reputation and cooperation in human groups KR McKee, E Hughes, TO Zhu, MJ Chadwick, R Koster, AG Castaneda, ... arXiv preprint arXiv:2103.04982, 2021 | 8 | 2021 |
Uncovering Surprising Behaviors in Reinforcement Learning via Worst-case Analysis.(2018) A Ruderman, R Everett, B Sikder, H Soyer, J Uesato, A Kumar, C Beattie, ... URL https://openreview. net/forum, 2018 | 3 | 2018 |
Vector-based navigation using grid-like representations in artificial agents A Pritzel, A Banino, B Uria, BC Zhang, C Barry, C Blundell, C Beattie, ... | 2 | 2018 |
Whatsapp Us M Jaderberg, WM Czarnecki, I Dunning, L Marris, G Lever, AG Castaneda, ... | | |
Appendix for: Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot JZ Leibo, E Duénez-Guzmán, AS Vezhnevets, JP Agapiou, P Sunehag, ... | | |