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Tom Schaul
Tom Schaul
Senior Staff Scientist, DeepMind
Zweryfikowany adres z nyu.edu - Strona główna
Tytuł
Cytowane przez
Cytowane przez
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Prioritized Experience Replay
T Schaul, J Quan, I Antonoglou, D Silver
International Conference on Learning Representations (ICLR), 2016
38562016
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
37632016
Grandmaster level in StarCraft II using multi-agent reinforcement learning
O Vinyals, I Babuschkin, WM Czarnecki, M Mathieu, A Dudzik, J Chung, ...
Nature 575 (7782), 350–354, 2019
31072019
Rainbow: Combining Improvements in Deep Reinforcement Learning
M Hessel, J Modayil, H Van Hasselt, T Schaul, G Ostrovski, W Dabney, ...
AAAI Conference on Artificial Intelligence, 2018
20742018
Learning to learn by gradient descent by gradient descent
M Andrychowicz, M Denil, S Gomez, MW Hoffman, D Pfau, T Schaul, ...
Neural Information Processing Systems (NeurIPS), 2016
19252016
Unifying Count-Based Exploration and Intrinsic Motivation
MG Bellemare, S Srinivasan, G Ostrovski, T Schaul, D Saxton, R Munos
Neural Information Processing Systems (NeurIPS), 2016
13572016
Reinforcement learning with unsupervised auxiliary tasks
M Jaderberg, V Mnih, WM Czarnecki, T Schaul, JZ Leibo, D Silver, ...
International Conference on Learning Representations (ICLR), 2017
12102017
Universal value function approximators
T Schaul, D Horgan, K Gregor, D Silver
International Conference on Machine Learning (ICML-15), 1312-1320, 2015
9852015
Deep Q-learning from Demonstrations
T Hester, M Vecerik, O Pietquin, M Lanctot, T Schaul, B Piot, D Horgan, ...
AAAI Conference on Artificial Intelligence, 2018
9702018
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
9142017
Natural evolution strategies
D Wierstra, T Schaul, T Glasmachers, Y Sun, J Peters, J Schmidhuber
The Journal of Machine Learning Research 15 (1), 949-980, 2014
8662014
Feudal networks for hierarchical reinforcement learning
AS Vezhnevets, S Osindero, T Schaul, N Heess, M Jaderberg, D Silver, ...
International Conference on Machine Learning (ICML), 2017
8462017
No more pesky learning rates
T Schaul, S Zhang, Y LeCun
International Conference on Machine Learning (ICML'13), 2013
5242013
AlphaStar: Mastering the Real-Time Strategy Game StarCraft II
O Vinyals, I Babuschkin, J Chung, M Mathieu, M Jaderberg, W Czarnecki, ...
(DeepMind blog), 2019
4972019
Successor features for transfer in reinforcement learning
A Barreto, W Dabney, R Munos, J Hunt, T Schaul, D Silver, H van Hasselt
Neural Information Processing Systems (NeurIPS), 2017
4742017
PyBrain
T Schaul, J Bayer, D Wierstra, Y Sun, M Felder, F Sehnke, T Rückstieß, ...
Journal of Machine Learning Research 11 (Feb), 743-746, 2010
4702010
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
300*2017
The 2014 General Video Game Playing Competition
D Perez, S Samothrakis, J Togelius, T Schaul, S Lucas, A Couëtoux, ...
Computational Intelligence and AI in Games, 2015
269*2015
A video game description language for model-based or interactive learning
T Schaul
Conference on Computational Intelligence in Games (IEEE-CIG), 1-8, 2013
2492013
General Video Game AI: Competition, Challenges and Opportunities
D Perez-Liebana, S Samothrakis, J Togelius, T Schaul, SM Lucas
AAAI What's Hot, 2016
2082016
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