Human-level control through deep reinforcement learning V Mnih, K Kavukcuoglu, D Silver, AA Rusu, J Veness, MG Bellemare, ...
nature 518 (7540), 529-533, 2015
11908 2015 The Arcade Learning Environment: An Evaluation Platform for General Agents MG Bellemare, Y Naddaf, J Veness, M Bowling
Journal of Artificial Intelligence Research 47, 253--279, 2013
1535 2013 Unifying count-based exploration and intrinsic motivation M Bellemare, S Srinivasan, G Ostrovski, T Schaul, D Saxton, R Munos
Advances in neural information processing systems, 1471-1479, 2016
623 2016 A distributional perspective on reinforcement learning MG Bellemare, W Dabney, R Munos
arXiv preprint arXiv:1707.06887, 2017
467 2017 Safe and efficient off-policy reinforcement learning R Munos, T Stepleton, A Harutyunyan, M Bellemare
Advances in Neural Information Processing Systems, 1054-1062, 2016
315 2016 Count-based exploration with neural density models G Ostrovski, MG Bellemare, A Oord, R Munos
arXiv preprint arXiv:1703.01310, 2017
248 2017 An introduction to deep reinforcement learning V François-Lavet, P Henderson, R Islam, MG Bellemare, J Pineau
arXiv preprint arXiv:1811.12560, 2018
233 2018 Revisiting the arcade learning environment: Evaluation protocols and open problems for general agents MC Machado, MG Bellemare, E Talvitie, J Veness, M Hausknecht, ...
Journal of Artificial Intelligence Research 61, 523-562, 2018
208 2018 Automated curriculum learning for neural networks A Graves, MG Bellemare, J Menick, R Munos, K Kavukcuoglu
arXiv preprint arXiv:1704.03003, 2017
198 2017 The cramer distance as a solution to biased wasserstein gradients MG Bellemare, I Danihelka, W Dabney, S Mohamed, ...
arXiv preprint arXiv:1705.10743, 2017
150 2017 Distributional reinforcement learning with quantile regression W Dabney, M Rowland, MG Bellemare, R Munos
arXiv preprint arXiv:1710.10044, 2017
134 2017 A laplacian framework for option discovery in reinforcement learning MC Machado, MG Bellemare, M Bowling
arXiv preprint arXiv:1703.00956, 2017
122 2017 Increasing the action gap: New operators for reinforcement learning MG Bellemare, G Ostrovski, A Guez, PS Thomas, R Munos
arXiv preprint arXiv:1512.04860, 2015
88 2015 Dopamine: A research framework for deep reinforcement learning PS Castro, S Moitra, C Gelada, S Kumar, MG Bellemare
arXiv preprint arXiv:1812.06110, 2018
79 2018 Investigating Contingency Awareness Using Atari 2600 Games. MG Bellemare, J Veness, M Bowling
AAAI, 2012
70 2012 Constructing evidence-based treatment strategies using methods from computer science J Pineau, MG Bellemare, AJ Rush, A Ghizaru, SA Murphy
Drug and alcohol dependence 88, S52-S60, 2007
68 2007 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
63 2020 The reactor: A sample-efficient actor-critic architecture A Gruslys, MG Azar, MG Bellemare, R Munos
arXiv preprint arXiv:1704.04651 5, 2017
49 2017 Q( A Harutyunyan, MG Bellemare, T Stepleton, R Munos
International Conference on Algorithmic Learning Theory, 305-320, 2016
43 2016 & Petersen, S.(2015). Human-level control through deep reinforcement learning V Mnih, K Kavukcuoglu, D Silver, AA Rusu, J Veness, MG Bellemare
Nature 518 (7540), 529, 0
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Joel VenessGoogle DeepMindGeverifieerd e-mailadres voor google.com
