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 | 2125 | 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 | 949 | 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 | 726 | 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 | 296 | 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 | 150 | 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 | 136 | 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 | 96 | 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 | 60 | 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 | 46 | 2019 |
Value propagation networks N Nardelli, G Synnaeve, Z Lin, P Kohli, PHS Torr, N Usunier arXiv preprint arXiv:1805.11199, 2018 | 34 | 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 | 30 | 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 | 28 | 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 | 19 | 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 | 17 | 2022 |
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 | 7 | 2020 |
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 | 5 | 2020 |
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 | | 2023 |
3.7 The Leonardo Project: Open-ended skill discovery S Risi, A Blair, B Bouzy, N Nardelli, T Schaul Artificial and Computational Intelligence in Games: Revolutions in …, 2019 | | 2019 |
Inference and Distillation for Option Learning M Igl, W Boehmer, A Gambardella, PHS Torr, N Nardelli, N Siddharth, ... Workshop on Probabilistic Reinforcement Learning and Structured Control …, 2018 | | 2018 |
Team Edinferno Description Paper for RoboCup 2013 SPL A Valtazanos, E Vafeias, AB Mico, D Mankowitz, N Nardelli, ... | | |