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Hado van Hasselt
Hado van Hasselt
Research Scientist, DeepMind; Honorary Professor, UCL
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Deep reinforcement learning with double Q-learning
H van Hasselt, A Guez, D Silver
AAAI Conference on Artificial Intelligence, 2094-2100, 2016
100672016
Dueling Network Architectures for Deep Reinforcement Learning
Z Wang, T Schaul, M Hessel, H van Hasselt, M Lanctot, N de Freitas
The 33rd International Conference on Machine Learning, 1995–2003, 2016
53832016
Rainbow: Combining improvements in deep reinforcement learning
M Hessel, J Modayil, H van Hasselt, T Schaul, G Ostrovski, W Dabney, ...
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
28502018
Double Q-learning
H van Hasselt
Advances in Neural Information Processing Systems, 2613-2621, 2010
2303*2010
Starcraft ii: A new challenge for reinforcement learning
O Vinyals, T Ewalds, S Bartunov, P Georgiev, AS Vezhnevets, M Yeo, ...
arXiv preprint arXiv:1708.04782, 2017
11182017
Distributed prioritized experience replay
D Horgan, J Quan, D Budden, G Barth-Maron, M Hessel, H van Hasselt, ...
arXiv preprint arXiv:1803.00933, 2018
9432018
Deep Reinforcement Learning in Large Discrete Action Spaces
G Dulac-Arnold, R Evans, H van Hasselt, P Sunehag, T Lillicrap, J Hunt
7732015
Successor features for transfer in reinforcement learning
A Barreto, W Dabney, R Munos, JJ Hunt, T Schaul, HP van Hasselt, ...
Advances in neural information processing systems 30, 2017
6802017
Meta-gradient reinforcement learning
Z Xu, HP van Hasselt, D Silver
Advances in neural information processing systems 31, 2018
3742018
Reinforcement learning in continuous action spaces
H van Hasselt, MA Wiering
Approximate Dynamic Programming and Reinforcement Learning, 2007. ADPRL 2007 …, 2007
3352007
Multi-task deep reinforcement learning with popart
M Hessel, H Soyer, L Espeholt, W Czarnecki, S Schmitt, H Van Hasselt
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3796-3803, 2019
3252019
The predictron: End-to-end learning and planning
D Silver, H Hasselt, M Hessel, T Schaul, A Guez, T Harley, ...
International Conference on Machine Learning, 3191-3199, 2017
3182017
Reinforcement Learning in Continuous State and Action Spaces
H van Hasselt
Reinforcement Learning: State of the Art, 207-251, 2012
3112012
A theoretical and empirical analysis of Expected Sarsa
H van Seijen, H van Hasselt, S Whiteson, M Wiering
Adaptive Dynamic Programming and Reinforcement Learning, 2009. ADPRL'09 …, 2009
2972009
Deep reinforcement learning and the deadly triad
H van Hasselt, Y Doron, F Strub, M Hessel, N Sonnerat, J Modayil
arXiv preprint arXiv:1812.02648, 2018
2772018
Ensemble algorithms in reinforcement learning
MA Wiering, H van Hasselt
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 38 …, 2008
2592008
When to use parametric models in reinforcement learning?
HP Van Hasselt, M Hessel, J Aslanides
Advances in Neural Information Processing Systems 32, 2019
2312019
Learning values across many orders of magnitude
H van Hasselt, A Guez, M Hessel, V Mnih, D Silver
Advances in Neural Information Processing Systems 29 (NIPS 2016), 2016
2082016
Behaviour suite for reinforcement learning
I Osband, Y Doron, M Hessel, J Aslanides, E Sezener, A Saraiva, ...
arXiv preprint arXiv:1908.03568, 2019
1922019
Weighted importance sampling for off-policy learning with linear function approximation
AR Mahmood, H van Hasselt, RS Sutton
Advances in Neural Information Processing Systems 27, 2014
1852014
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