Marc G. Bellemare
Marc G. Bellemare
Google Brain
Verified email at - Homepage
Cited by
Cited by
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
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
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
A distributional perspective on reinforcement learning
MG Bellemare, W Dabney, R Munos
arXiv preprint arXiv:1707.06887, 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
Count-based exploration with neural density models
G Ostrovski, MG Bellemare, A Oord, R Munos
arXiv preprint arXiv:1703.01310, 2017
An introduction to deep reinforcement learning
V François-Lavet, P Henderson, R Islam, MG Bellemare, J Pineau
arXiv preprint arXiv:1811.12560, 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
Automated curriculum learning for neural networks
A Graves, MG Bellemare, J Menick, R Munos, K Kavukcuoglu
arXiv preprint arXiv:1704.03003, 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
Distributional reinforcement learning with quantile regression
W Dabney, M Rowland, MG Bellemare, R Munos
arXiv preprint arXiv:1710.10044, 2017
A laplacian framework for option discovery in reinforcement learning
MC Machado, MG Bellemare, M Bowling
arXiv preprint arXiv:1703.00956, 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
Dopamine: A research framework for deep reinforcement learning
PS Castro, S Moitra, C Gelada, S Kumar, MG Bellemare
arXiv preprint arXiv:1812.06110, 2018
Investigating Contingency Awareness Using Atari 2600 Games.
MG Bellemare, J Veness, M Bowling
AAAI, 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
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
The reactor: A sample-efficient actor-critic architecture
A Gruslys, MG Azar, MG Bellemare, R Munos
arXiv preprint arXiv:1704.04651 5, 2017
Q() with Off-Policy Corrections
A Harutyunyan, MG Bellemare, T Stepleton, R Munos
International Conference on Algorithmic Learning Theory, 305-320, 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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