Stebėti
Andre Barreto
Andre Barreto
Research Scientist, Google DeepMind
Patvirtintas el. paštas google.com - Pagrindinis puslapis
Pavadinimas
Cituota
Cituota
Metai
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
6012017
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
3002017
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
1852018
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
1562019
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
1492021
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
1362020
Universal successor features approximators
D Borsa, A Barreto, J Quan, D Mankowitz, R Munos, H Van Hasselt, ...
arXiv preprint arXiv:1812.07626, 2018
1242018
Value-aware loss function for model-based reinforcement learning
A Farahmand, A Barreto, D Nikovski
Artificial Intelligence and Statistics, 1486-1494, 2017
1212017
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
962019
Temporally-extended {\epsilon}-greedy exploration
W Dabney, G Ostrovski, A Barreto
arXiv preprint arXiv:2006.01782, 2020
932020
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
772020
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
722008
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
672021
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
662010
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
612001
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
512011
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
462018
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
462002
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
452021
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Straipsniai 1–20