Suivre
Andre Barreto
Andre Barreto
Research Scientist, Google DeepMind
Adresse e-mail validée de google.com - Page d'accueil
Titre
Citée par
Citée par
Année
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
6442017
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
3082017
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
2012018
New machine learning and physics-based scoring functions for drug discovery
IA Guedes, AMS Barreto, D Marinho, E Krempser, MA Kuenemann, ...
Scientific reports 11 (1), 3198, 2021
1712021
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
1682019
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
1422020
Universal successor features approximators
D Borsa, A Barreto, J Quan, D Mankowitz, R Munos, H Van Hasselt, ...
arXiv preprint arXiv:1812.07626, 2018
1332018
Value-aware loss function for model-based reinforcement learning
A Farahmand, A Barreto, D Nikovski
Artificial Intelligence and Statistics, 1486-1494, 2017
1302017
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
1042019
Temporally-extended {\epsilon}-greedy exploration
W Dabney, G Ostrovski, A Barreto
arXiv preprint arXiv:2006.01782, 2020
1032020
The value equivalence principle for model-based reinforcement learning
C Grimm, A Barreto, S Singh, D Silver
Advances in neural information processing systems 33, 5541-5552, 2020
822020
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
732008
The value-improvement path: Towards better representations for reinforcement learning
W Dabney, A Barreto, M Rowland, R Dadashi, J Quan, MG Bellemare, ...
Proceedings of the AAAI Conference on Artificial Intelligence 35 (8), 7160-7168, 2021
712021
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
712010
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
Practical kernel-based reinforcement learning
AMS Barreto, D Precup, J Pineau
Journal of Machine Learning Research 17 (67), 1-70, 2016
522016
Reinforcement learning using kernel-based stochastic factorization
A Barreto, D Precup, J Pineau
Advances in Neural Information Processing Systems 24, 2011
522011
Temporal abstraction in reinforcement learning with the successor representation
MC Machado, A Barreto, D Precup, M Bowling
Journal of Machine Learning Research 24 (80), 1-69, 2023
492023
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
492018
Expected eligibility traces
H van Hasselt, S Madjiheurem, M Hessel, D Silver, A Barreto, D Borsa
Proceedings of the AAAI conference on artificial intelligence 35 (11), 9997 …, 2021
482021
Le système ne peut pas réaliser cette opération maintenant. Veuillez réessayer plus tard.
Articles 1–20