Mastering the game of Go with deep neural networks and tree search D Silver, A Huang, CJ Maddison, A Guez, L Sifre, G Van Den Driessche, ... nature 529 (7587), 484-489, 2016 | 14879 | 2016 |
Mastering the game of go without human knowledge D Silver, J Schrittwieser, K Simonyan, I Antonoglou, A Huang, A Guez, ... nature 550 (7676), 354-359, 2017 | 8334 | 2017 |
A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play D Silver, T Hubert, J Schrittwieser, I Antonoglou, M Lai, A Guez, M Lanctot, ... Science 362 (6419), 1140-1144, 2018 | 2932 | 2018 |
Mastering chess and shogi by self-play with a general reinforcement learning algorithm D Silver, T Hubert, J Schrittwieser, I Antonoglou, M Lai, A Guez, M Lanctot, ... arXiv preprint arXiv:1712.01815, 2017 | 1598 | 2017 |
Mastering atari, go, chess and shogi by planning with a learned model J Schrittwieser, I Antonoglou, T Hubert, K Simonyan, L Sifre, S Schmitt, ... Nature 588 (7839), 604-609, 2020 | 1285 | 2020 |
Starcraft ii: A new challenge for reinforcement learning O Vinyals, T Ewalds, S Bartunov, P Georgiev, AS Vezhnevets, M Yeo, ... arXiv preprint arXiv:1708.04782, 2017 | 804 | 2017 |
Deepmind lab C Beattie, JZ Leibo, D Teplyashin, T Ward, M Wainwright, H Küttler, ... arXiv preprint arXiv:1612.03801, 2016 | 465 | 2016 |
& Chen, Y.(2017). Mastering the game of go without human knowledge D Silver, J Schrittwieser, K Simonyan, I Antonoglou, A Huang, A Guez Nature 550 (7676), 354, 0 | 172 | |
OpenSpiel: A framework for reinforcement learning in games M Lanctot, E Lockhart, JB Lespiau, V Zambaldi, S Upadhyay, J Pérolat, ... arXiv preprint arXiv:1908.09453, 2019 | 148 | 2019 |
Bayesian optimization in alphago Y Chen, A Huang, Z Wang, I Antonoglou, J Schrittwieser, D Silver, ... arXiv preprint arXiv:1812.06855, 2018 | 106 | 2018 |
Competition-level code generation with alphacode Y Li, D Choi, J Chung, N Kushman, J Schrittwieser, R Leblond, T Eccles, ... Science 378 (6624), 1092-1097, 2022 | 95 | 2022 |
and Hassabis, D. 2016. Mastering the game of go with deep neural networks and tree search D Silver, A Huang, CJ Maddison, A Guez, L Sifre, G Van Den Driessche, ... Nature 529 (7587), 484-489, 0 | 58 | |
et almbox. 2016. Mastering the game of Go with deep neural networks and tree search D Silver, A Huang, CJ Maddison, A Guez, L Sifre, G Van Den Driessche, ... Nature 529 (7587), 484-489, 2016 | 54 | 2016 |
Online and offline reinforcement learning by planning with a learned model J Schrittwieser, T Hubert, A Mandhane, M Barekatain, I Antonoglou, ... Advances in Neural Information Processing Systems 34, 27580-27591, 2021 | 50 | 2021 |
Discovering faster matrix multiplication algorithms with reinforcement learning A Fawzi, M Balog, A Huang, T Hubert, B Romera-Paredes, M Barekatain, ... Nature 610 (7930), 47-53, 2022 | 38 | 2022 |
Panneershelvam Veda, Lanctot Marc, et al S David, H Aja, J Maddison Chris, G Arthur, S Laurent, ... Mastering the game of go with deep neural networks and tree search. Nature …, 2016 | 36 | 2016 |
Learning and planning in complex action spaces T Hubert, J Schrittwieser, I Antonoglou, M Barekatain, S Schmitt, D Silver International Conference on Machine Learning, 4476-4486, 2021 | 26 | 2021 |
Procedural generalization by planning with self-supervised world models A Anand, J Walker, Y Li, E Vértes, J Schrittwieser, S Ozair, T Weber, ... arXiv preprint arXiv:2111.01587, 2021 | 17 | 2021 |
Approximate exploitability: Learning a best response in large games F Timbers, N Bard, E Lockhart, M Lanctot, M Schmid, N Burch, ... arXiv preprint arXiv:2004.09677, 2020 | 14 | 2020 |
Local search for policy iteration in continuous control JT Springenberg, N Heess, D Mankowitz, J Merel, A Byravan, ... arXiv preprint arXiv:2010.05545, 2020 | 11 | 2020 |