| Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning T Rashid, M Samvelyan, CS De Witt, G Farquhar, J Foerster, S Whiteson JMLR, 2020 | 3803 | 2020 |
| Counterfactual Multi-Agent Policy Gradients J Foerster, G Farquhar, T Afouras, N Nardelli, S Whiteson AAAI 2018, Outstanding Student Paper Award, 2017 | 3106 | 2017 |
| Learning to communicate with deep multi-agent reinforcement learning J Foerster, YM Assael, N de Freitas, S Whiteson Advances in Neural Information Processing Systems., 2137--2145, 2016 | 2553 | 2016 |
| 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, P Torr, P Kohli, S Whiteson International Conference on Machine Learning, 2017, 2017 | 896 | 2017 |
| Learning with opponent-learning awareness J Foerster, RY Chen, M Al-Shedivat, S Whiteson, P Abbeel, I Mordatch Proceedings of the 17th International Conference on Autonomous Agents and …, 2018 | 771 | 2018 |
| The ai scientist: Towards fully automated open-ended scientific discovery C Lu, C Lu, RT Lange, J Foerster, J Clune, D Ha arXiv preprint arXiv:2408.06292, 2024 | 594 | 2024 |
| The hanabi challenge: A new frontier for ai research N Bard, JN Foerster, S Chandar, N Burch, M Lanctot, HF Song, E Parisotto, ... Artificial Intelligence 280, 103216, 2020 | 551 | 2020 |
| Hotword recognition M Sharifi, JN Foerster US Patent 9,928,840, 2018 | 526 | 2018 |
| The Mechanics of n-Player Differentiable Games D Balduzzi, S Racaniere, J Martens, J Foerster, K Tuyls, T Graepel Proceedings of the 35th International Conference on Machine Learning, 2018 | 376 | 2018 |
| Hotword detection on multiple devices DM Casado, AH Gruenstein, JN Foerster US Patent 9,972,320, 2018 | 374* | 2018 |
| 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 |
| Dynamic threshold for speaker verification J Foerster, DM Casado US Patent 9,384,738, 2016 | 315 | 2016 |
| Foundational challenges in assuring alignment and safety of large language models U Anwar, A Saparov, J Rando, D Paleka, M Turpin, P Hase, ES Lubana, ... arXiv preprint arXiv:2404.09932, 2024 | 296 | 2024 |
| Three-dimensional head-direction coding in the bat brain A Finkelstein, D Derdikman, A Rubin, JN Foerster, L Las, N Ulanovsky Nature 517 (7533), 159-164, 2015 | 290 | 2015 |
| Exploratory combinatorial optimization with reinforcement learning TD Barrett, WR Clements, JN Foerster, AI Lvovsky AAAI 2020, 2019 | 285 | 2019 |
| "Other-Play" for Zero-Shot Coordination H Hu, A Lerer, A Peysakhovich, J Foerster ICML 2020, 2020 | 278 | 2020 |
| Smacv2: An improved benchmark for cooperative multi-agent reinforcement learning B Ellis, J Cook, S Moalla, M Samvelyan, M Sun, A Mahajan, J Foerster, ... Advances in Neural Information Processing Systems 36, 37567-37593, 2023 | 222 | 2023 |
| Bayesian action decoder for deep multi-agent reinforcement learning JN Foerster, F Song, E Hughes, N Burch, I Dunning, S Whiteson, ... ICML 2019, 2018 | 220 | 2018 |
| Evolving curricula with regret-based environment design J Parker-Holder, M Jiang, M Dennis, M Samvelyan, J Foerster, ... International Conference on Machine Learning, 17473-17498, 2022 | 198 | 2022 |
Shimon WhitesonProfessor of Computer Science, University of Oxford / Senior Staff Research Scientist, WaymoVerified email at cs.ox.ac.uk
