| Counterfactual multi-agent policy gradients J Foerster, G Farquhar, T Afouras, N Nardelli, S Whiteson Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 3106 | 2018 |
| The starcraft multi-agent challenge M Samvelyan, T Rashid, CS De Witt, G Farquhar, N Nardelli, TGJ Rudner, ... arXiv preprint arXiv:1902.04043, 2019 | 1544 | 2019 |
| Stabilising experience replay for deep multi-agent reinforcement learning J Foerster*, N Nardelli*, G Farquhar, T Afouras, PHS Torr, P Kohli, ... International conference on machine learning, 1146-1155, 2017 | 897 | 2017 |
| A survey of reinforcement learning informed by natural language J Luketina, N Nardelli, G Farquhar, J Foerster, J Andreas, E Grefenstette, ... arXiv preprint arXiv:1906.03926, 2019 | 372 | 2019 |
| The nethack learning environment H Küttler, N Nardelli, A Miller, R Raileanu, M Selvatici, E Grefenstette, ... Advances in Neural Information Processing Systems 33, 7671-7684, 2020 | 248 | 2020 |
| Torchcraft: a library for machine learning research on real-time strategy games G Synnaeve, N Nardelli, A Auvolat, S Chintala, T Lacroix, Z Lin, F Richoux, ... arXiv preprint arXiv:1611.00625, 2016 | 148 | 2016 |
| Playing doom with slam-augmented deep reinforcement learning S Bhatti, A Desmaison, O Miksik, N Nardelli, N Siddharth, PHS Torr arXiv preprint arXiv:1612.00380, 2016 | 105 | 2016 |
| Torchbeast: A pytorch platform for distributed rl H Küttler, N Nardelli, T Lavril, M Selvatici, V Sivakumar, T Rocktäschel, ... arXiv preprint arXiv:1910.03552, 2019 | 72 | 2019 |
| Mvfst-rl: An asynchronous rl framework for congestion control with delayed actions V Sivakumar, O Delalleau, T Rocktäschel, AH Miller, H Küttler, N Nardelli, ... arXiv preprint arXiv:1910.04054, 2019 | 59 | 2019 |
| Value propagation networks N Nardelli, G Synnaeve, Z Lin, P Kohli, PHS Torr, N Usunier arXiv preprint arXiv:1805.11199, 2018 | 39 | 2018 |
| Multitask soft option learning M Igl, A Gambardella, J He, N Nardelli, N Siddharth, W Böhmer, ... Conference on uncertainty in artificial intelligence, 969-978, 2020 | 35 | 2020 |
| Counterfactual reasoning about intent for interactive navigation in dynamic environments A Bordallo, F Previtali, N Nardelli, S Ramamoorthy 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015 | 33 | 2015 |
| Wordcraft: An environment for benchmarking commonsense agents M Jiang, J Luketina, N Nardelli, P Minervini, PHS Torr, S Whiteson, ... arXiv preprint arXiv:2007.09185, 2020 | 26 | 2020 |
| Insights from the neurips 2021 nethack challenge E Hambro, S Mohanty, D Babaev, M Byeon, D Chakraborty, ... NeurIPS 2021 Competitions and Demonstrations Track, 41-52, 2022 | 25 | 2022 |
| Lessons from reinforcement learning for biological representations of space A Muryy, N Siddharth, N Nardelli, A Glennerster, PHS Torr Vision Research 174, 79-93, 2020 | 9 | 2020 |
| Simulation-based inference for global health decisions CS de Witt, B Gram-Hansen, N Nardelli, A Gambardella, R Zinkov, ... arXiv preprint arXiv:2005.07062, 2020 | 9 | 2020 |
| Affordable, manageable, practical, and scalable (AMPS) high-yield and high-gain inertial fusion A Alexander, LR Benedetti, I Bhattacharyya, J Bowen, J Cabatu, ... Physics of Plasmas 32 (9), 2025 | 7 | 2025 |
| Validation of FLASH for magnetically driven inertial confinement fusion target design CL Ellison, J Carroll-Nellenback, C Chen, S Davidson, B Ferguson, ... Physics of Plasmas 32 (9), 2025 | 6 | 2025 |
| Can Reinforcement Learning support policy makers? A preliminary study with Integrated Assessment Models T Wolf, N Nardelli, J Shawe-Taylor, M Perez-Ortiz arXiv preprint arXiv:2312.06527, 2023 | 5 | 2023 |
| Analysis of Preheat Propagation in MagLIF-like Plasmas F Garcia-Rubio, S Davidson, CL Ellison, NB Meezan, DS Miller, ... arXiv preprint arXiv:2504.11432, 2025 | | 2025 |
Shimon WhitesonProfessor of Computer Science, University of Oxford / Senior Staff Research Scientist, WaymoVerified email at cs.ox.ac.uk
