| Dueling Network Architectures for Deep Reinforcement Learning Z Wang, T Schaul, M Hessel, H Van Hasselt, M Lanctot, N De Freitas International Conference on Machine Learning (ICML 2016), 1995–2003, 2016 | 2913 | 2016 |
| Rainbow: Combining Improvements in Deep Reinforcement Learning M Hessel, J Modayil, H van Hasselt, T Schaul, G Ostrovski, W Dabney, ... Association for the Advancement of Artificial Intelligence (AAAI 2018), 2017 | 1583 | 2017 |
| Distributed Prioritized Experience Replay D Horgan, J Quan, D Budden, G Barth-Maron, M Hessel, H van Hasselt, ... International Conference on Learning Representations (ICLR 2018), 2018 | 546 | 2018 |
| Noisy networks for exploration M Fortunato, MG Azar, B Piot, J Menick, M Hessel, I Osband, A Graves, ... International Conference on Learning Representations (ICLR 2018), 2017 | 447 | 2017 |
| The predictron: End-to-end learning and planning D Silver, H van Hasselt, M Hessel, T Schaul, A Guez, T Harley, ... International Conference on Machine Learning (ICML 2017), 3191--3199, 2016 | 238 | 2016 |
| Multi-task Deep Reinforcement Learning with PopArt M Hessel, H Soyer, L Espeholt, W Czarnecki, S Schmitt, H van Hasselt Association for the Advancement of Artificial Intelligence (AAAI 2019), 2018 | 169 | 2018 |
| Learning values across many orders of magnitude HP van Hasselt, A Guez, M Hessel, V Mnih, D Silver Advances In Neural Information Processing Systems (NIPS 2016), 4287-4295, 2016 | 137 | 2016 |
| Deep Reinforcement Learning and the Deadly Triad H van Hasselt, Y Doron, F Strub, M Hessel, N Sonnerat, J Modayil Deep Reinforcement Learning Workshop (NeurIPS 2018), 2018 | 134 | 2018 |
| Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement A Barreto, D Borsa, J Quan, T Schaul, D Silver, M Hessel, D Mankowitz, ... International Conference on Machine Learning (ICML 2018), 510-519, 2018 | 115 | 2018 |
| When to use parametric models in reinforcement learning? HP van Hasselt, M Hessel, J Aslanides Advances in Neural Information Processing Systems (NeurIPS 2019), 2019 | 111 | 2019 |
| Behaviour Suite for Reinforcement Learning I Osband, Y Doron, M Hessel, J Aslanides, E Sezener, A Saraiva, ... International Conference on Learning Representations (ICLR 2020), 2019 | 105 | 2019 |
| Observe and Look Further: Achieving Consistent Performance on Atari T Pohlen, B Piot, T Hester, MG Azar, D Horgan, D Budden, G Barth-Maron, ... arXiv preprint arXiv:1805.11593, 2018 | 75 | 2018 |
| Discovery of useful questions as auxiliary tasks V Veeriah, M Hessel, Z Xu, J Rajendran, RL Lewis, J Oh, HP van Hasselt, ... Advances in Neural Information Processing Systems (NeurIPS 2019), 9310-9321, 2019 | 62 | 2019 |
| Discovering reinforcement learning algorithms J Oh, M Hessel, WM Czarnecki, Z Xu, HP van Hasselt, S Singh, D Silver Advances in Neural Information Processing Systems 33, 1060-1070, 2020 | 52 | 2020 |
| Self-tuning deep reinforcement learning T Zahavy, Z Xu, V Veeriah, M Hessel, J Oh, H van Hasselt, D Silver, ... arXiv preprint arXiv:2002.12928, 2020 | 43* | 2020 |
| What Can Learned Intrinsic Rewards Capture? Z Zheng, J Oh, M Hessel, Z Xu, M Kroiss, H van Hasselt, D Silver, S Singh International Conference on Machine Learning (ICML 2020), 0 | 38* | |
| Meta-gradient reinforcement learning with an objective discovered online Z Xu, HP van Hasselt, M Hessel, J Oh, S Singh, D Silver Advances in Neural Information Processing Systems 33, 15254-15264, 2020 | 36 | 2020 |
| Unicorn: Continual Learning with a Universal, Off-policy Agent DJ Mankowitz, A Žídek, A Barreto, D Horgan, M Hessel, J Quan, J Oh, ... Multi-disciplinary Conference on Reinforcement Learning and Decision Making …, 2018 | 36 | 2018 |
| Off-Policy Actor-Critic with Shared Experience Replay S Schmitt, M Hessel, K Simonyan International Conference on Machine Learning (ICML 2020), 2019 | 31 | 2019 |
| On inductive biases in deep reinforcement learning M Hessel, H van Hasselt, J Modayil, D Silver Multi-disciplinary Conference on Reinforcement Learning and Decision Making …, 2019 | 31 | 2019 |
Hado van HasseltResearch Scientist, DeepMind; Honorary Professor, UCLDirección de correo verificada de google.com
