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Andre Barreto
Andre Barreto
Research Scientist, Google DeepMind
Adresse e-mail validée de google.com - Page d'accueil
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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
3712017
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
2352017
Transfer in deep reinforcement learning using successor features and generalised policy improvement
A Barreto, D Borsa, J Quan, T Schaul, D Silver, M Hessel, D Mankowitz, ...
International Conference on Machine Learning, 501-510, 2018
1102018
Fast task inference with variational intrinsic successor features
S Hansen, W Dabney, A Barreto, T Van de Wiele, D Warde-Farley, V Mnih
arXiv preprint arXiv:1906.05030, 2019
692019
Restricted gradient-descent algorithm for value-function approximation in reinforcement learning
A da Motta Salles Barreto, CW Anderson
Artificial Intelligence 172 (4-5), 454-482, 2008
652008
Universal successor features approximators
D Borsa, A Barreto, J Quan, D Mankowitz, R Munos, H Van Hasselt, ...
arXiv preprint arXiv:1812.07626, 2018
642018
Value-aware loss function for model-based reinforcement learning
A Farahmand, A Barreto, D Nikovski
Artificial Intelligence and Statistics, 1486-1494, 2017
602017
An interactive genetic algorithm with co-evolution of weights for multiobjective problems
HJC Barbosa, AMS Barreto
Proceedings of the 3rd Annual Conference on Genetic and Evolutionary …, 2001
602001
Using performance profiles to analyze the results of the 2006 CEC constrained optimization competition
HJC Barbosa, HS Bernardino, AMS Barreto
IEEE congress on evolutionary computation, 1-8, 2010
522010
Fast reinforcement learning with generalized policy updates
A Barreto, S Hou, D Borsa, D Silver, D Precup
Proceedings of the National Academy of Sciences 117 (48), 30079-30087, 2020
492020
Growing compact RBF networks using a genetic algorithm
AMS Barreto, HJC Barbosa, NFF Ebecken
VII Brazilian Symposium on Neural Networks, 2002. SBRN 2002. Proceedings., 61-66, 2002
412002
Reinforcement learning using kernel-based stochastic factorization
A Barreto, D Precup, J Pineau
Advances in Neural Information Processing Systems 24, 2011
382011
The option keyboard: Combining skills in reinforcement learning
A Barreto, D Borsa, S Hou, G Comanici, E Aygün, P Hamel, D Toyama, ...
Advances in Neural Information Processing Systems 32, 2019
372019
Practical kernel-based reinforcement learning
AMS Barreto, D Precup, J Pineau
The Journal of Machine Learning Research 17 (1), 2372-2441, 2016
372016
Unicorn: Continual learning with a universal, off-policy agent
DJ Mankowitz, A Žídek, A Barreto, D Horgan, M Hessel, J Quan, J Oh, ...
arXiv preprint arXiv:1802.08294, 2018
352018
Fast deep reinforcement learning using online adjustments from the past
S Hansen, A Pritzel, P Sprechmann, A Barreto, C Blundell
Advances in Neural Information Processing Systems 31, 2018
332018
GOLS—Genetic orthogonal least squares algorithm for training RBF networks
AMS Barreto, HJC Barbosa, NFF Ebecken
Neurocomputing 69 (16-18), 2041-2064, 2006
312006
Graph layout using a genetic algorithm
AMS Barreto, HJC Barbosa
Proceedings. Vol. 1. Sixth Brazilian Symposium on Neural Networks, 179-184, 2000
292000
Temporally-extended {\epsilon}-greedy exploration
W Dabney, G Ostrovski, A Barreto
arXiv preprint arXiv:2006.01782, 2020
242020
A note on the variance of rank-based selection strategies for genetic algorithms and genetic programming
A Sokolov, D Whitley, A da Motta Salles Barreto
Genetic Programming and Evolvable Machines 8 (3), 221-237, 2007
222007
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