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Andre Barreto
Andre Barreto
Research Scientist, Google DeepMind
Bestätigte E-Mail-Adresse bei google.com - Startseite
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Zitiert von
Zitiert von
Jahr
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
6962017
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
3202017
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
2102018
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
2022021
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
1882019
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
1582020
Universal successor features approximators
D Borsa, A Barreto, J Quan, D Mankowitz, R Munos, H Van Hasselt, ...
arXiv preprint arXiv:1812.07626, 2018
1512018
Value-aware loss function for model-based reinforcement learning
A Farahmand, A Barreto, D Nikovski
Artificial Intelligence and Statistics, 1486-1494, 2017
1382017
Temporally-extended {\epsilon}-greedy exploration
W Dabney, G Ostrovski, A Barreto
arXiv preprint arXiv:2006.01782, 2020
1172020
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
1152019
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
912020
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
762021
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
742010
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
A definition of continual reinforcement learning
D Abel, A Barreto, B Van Roy, D Precup, HP van Hasselt, S Singh
Advances in Neural Information Processing Systems 36, 50377-50407, 2023
722023
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
622001
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
572023
Practical kernel-based reinforcement learning
AMS Barreto, D Precup, J Pineau
Journal of Machine Learning Research 17 (67), 1-70, 2016
552016
On efficiency in hierarchical reinforcement learning
Z Wen, D Precup, M Ibrahimi, A Barreto, B Van Roy, S Singh
Advances in Neural Information Processing Systems 33, 6708-6718, 2020
522020
Reinforcement learning using kernel-based stochastic factorization
A Barreto, D Precup, J Pineau
Advances in Neural Information Processing Systems 24, 2011
522011
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