Tom Schaul
TitleCited byYear
Prioritized Experience Replay
T Schaul, J Quan, I Antonoglou, D Silver
International Conference on Learning Representations (ICLR), 2016
8412016
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
7462016
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 (NIPS), 2016
5392016
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
4062017
Unifying Count-Based Exploration and Intrinsic Motivation
MG Bellemare, S Srinivasan, G Ostrovski, T Schaul, D Saxton, R Munos
Neural Information Processing Systems (NIPS), 2016
3732016
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
3672010
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
3142018
No more pesky learning rates
T Schaul, S Zhang, Y LeCun
International Conference on Machine Learning (ICML'13), 2013
2902013
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
2322017
Universal value function approximators
T Schaul, D Horgan, K Gregor, D Silver
International Conference on Machine Learning (ICML-15), 1312-1320, 2015
2222015
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
2162018
Natural evolution strategies
D Wierstra, T Schaul, J Peters, J Schmidhuber
IEEE Congress on Evolutionary Computation (IEEE World Congress on …, 2008
2072008
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
2022017
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
168*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
1512013
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
1432014
Exponential natural evolution strategies
T Glasmachers, T Schaul, S Yi, D Wierstra, J Schmidhuber
Genetic and evolutionary computation conference (GECCO), 393-400, 2010
1212010
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 (NIPS), 2017
1162017
General Video Game AI: Competition, Challenges and Opportunities
D Perez-Liebana, S Samothrakis, J Togelius, T Schaul, SM Lucas
AAAI What's Hot, 2016
1112016
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
1052017
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Articles 1–20