Georg Ostrovski
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
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
Hybrid computing using a neural network with dynamic external memory
A Graves, G Wayne, M Reynolds, T Harley, I Danihelka, ...
Nature 538 (7626), 471-476, 2016
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 29, 2016
Count-based exploration with neural density models
G Ostrovski, MG Bellemare, A Oord, R Munos
International conference on machine learning, 2721-2730, 2017
Implicit quantile networks for distributional reinforcement learning
W Dabney, G Ostrovski, D Silver, R Munos
International conference on machine learning, 1096-1105, 2018
Recurrent experience replay in distributed reinforcement learning
S Kapturowski, G Ostrovski, J Quan, R Munos, W Dabney
International conference on learning representations, 2018
Increasing the action gap: New operators for reinforcement learning
MG Bellemare, G Ostrovski, A Guez, P Thomas, R Munos
Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016
Autoregressive quantile networks for generative modeling
G Ostrovski, W Dabney, R Munos
International Conference on Machine Learning, 3936-3945, 2018
Symmetric decomposition of asymmetric games
K Tuyls, J Pérolat, M Lanctot, G Ostrovski, R Savani, JZ Leibo, T Ord, ...
Scientific reports 8 (1), 1-20, 2018
Temporally-extended {\epsilon}-greedy exploration
W Dabney, G Ostrovski, A Barreto
arXiv preprint arXiv:2006.01782, 2020
On the effect of auxiliary tasks on representation dynamics
C Lyle, M Rowland, G Ostrovski, W Dabney
International Conference on Artificial Intelligence and Statistics, 1-9, 2021
Payoff performance of fictitious play
G Ostrovski, S van Strien
Journal of Dynamics and Games 1 (4), 621-638, 2014
Payoff performance of fictitious play
G Ostrovski, S van Strien
arXiv preprint arXiv:1308.4049, 2013
Piecewise linear Hamiltonian flows associated to zero-sum games: transition combinatorics and questions on ergodicity
G Ostrovski, S van Strien
Regular and Chaotic Dynamics 16 (1), 128-153, 2011
Adapting behaviour for learning progress
T Schaul, D Borsa, D Ding, D Szepesvari, G Ostrovski, W Dabney, ...
arXiv preprint arXiv:1912.06910, 2019
The difficulty of passive learning in deep reinforcement learning
G Ostrovski, PS Castro, W Dabney
Advances in Neural Information Processing Systems 34, 23283-23295, 2021
Agnieszka Grabska-Barwi nska
A Graves, G Wayne, M Reynolds, T Harley, I Danihelka
Sergio Gómez Colmenarejo, Edward Grefenstette, Tiago Ramalho, John Agapiou …, 2016
When should agents explore?
M Pislar, D Szepesvari, G Ostrovski, D Borsa, T Schaul
arXiv preprint arXiv:2108.11811, 2021
Return-based scaling: Yet another normalisation trick for deep RL
T Schaul, G Ostrovski, I Kemaev, D Borsa
arXiv preprint arXiv:2105.05347, 2021
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