| 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 | 8939 | 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 | 3248 | 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 | 1733 | 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 | 1505 | 2020 |
| 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 | 202 | 2022 |
| 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 | 119 | 2022 |
| Cyprien de Masson d’Autume, Igor Babuschkin, Xinyun Chen, Po-Sen Huang, Johannes Welbl, Sven Gowal, Alexey Cherepanov, James Molloy, Daniel J Y Li, D Choi, J Chung, N Kushman, J Schrittwieser, R Leblond, T Eccles, ... Mankowitz, Esme Sutherland Robson, Pushmeet Kohli, Nando de Freitas, Koray …, 2022 | 66 | 2022 |
| 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 | 63 | 2021 |
| Monte-Carlo tree search as regularized policy optimization JB Grill, F Altché, Y Tang, T Hubert, M Valko, I Antonoglou, R Munos International Conference on Machine Learning, 3769-3778, 2020 | 53 | 2020 |
| 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 | 36 | 2021 |
| Planning in stochastic environments with a learned model I Antonoglou, J Schrittwieser, S Ozair, TK Hubert, D Silver International Conference on Learning Representations, 2021 | 18 | 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 | 17 | 2020 |
| Muzero with self-competition for rate control in vp9 video compression A Mandhane, A Zhernov, M Rauh, C Gu, M Wang, F Xue, W Shang, ... arXiv preprint arXiv:2202.06626, 2022 | 15 | 2022 |
| Approximate Exploitability: Learning a Best Response F Timbers, N Bard, E Lockhart, M Lanctot, M Schmid, N Burch, ... Proceedings of the International Joint Conference on Artificial Intelligence …, 2022 | 3 | 2022 |
| Lai D Silver, J Schrittwieser, K Simonyan, I Antonoglou, A Huang, A Guez, ... M., Bolton, A., Chen, Y., Lillicrap, T., Hui, F., Sifre, L., van den, 0 | 1 | |
| Optimizing Memory Mapping Using Deep Reinforcement Learning P Wang, M Sazanovich, B Ilbeyi, PM Phothilimthana, M Purohit, HY Tay, ... arXiv preprint arXiv:2305.07440, 2023 | | 2023 |
| Planning for agent control using learned hidden states J Schrittwieser, I Antonoglou, TK Hubert US Patent App. 17/794,797, 2023 | | 2023 |
