Andre Barreto
Andre Barreto
Research Scientist, Google DeepMind
Verified email at google.com - Homepage
TitleCited byYear
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, 4055-4065, 2017
1302017
The predictron: End-to-end learning and planning
D Silver, H van Hasselt, M Hessel, T Schaul, A Guez, T Harley, ...
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
1132017
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
552008
An interactive genetic algorithm with co-evolution of weights for multiobjective problems
HJC Barbosa, A Barreto
Proceedings of the 3rd Annual Conference on Genetic and Evolutionary …, 2001
532001
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
472010
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
392002
Reinforcement learning using kernel-based stochastic factorization
AS Barreto, D Precup, J Pineau
Advances in Neural Information Processing Systems, 720-728, 2011
322011
GOLS—genetic orthogonal least squares algorithm for training RBF networks
AMS Barreto, HJC Barbosa, NFF Ebecken
Neurocomputing 69 (16-18), 2041-2064, 2006
312006
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, ...
arXiv preprint arXiv:1901.10964, 2019
272019
Graph layout using a genetic algorithm
AMS Barreto, HJC Barbosa
Proceedings. Vol. 1. Sixth Brazilian Symposium on Neural Networks, 179-184, 2000
262000
A note on the variance of rank-based selection strategies for genetic algorithms and genetic programming
A Sokolov, D Whitley
Genetic Programming and Evolvable Machines 8 (3), 221-237, 2007
192007
Practical kernel-based reinforcement learning
A Barreto, D Precup, J Pineau
The Journal of Machine Learning Research 17 (1), 2372-2441, 2016
172016
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
142018
Policy iteration based on stochastic factorization
AMS Barreto, J Pineau, D Precup
Journal of Artificial Intelligence Research 50, 763-803, 2014
142014
Computing the stationary distribution of a finite Markov chain through stochastic factorization
AMS Barreto, MD Fragoso
SIAM Journal on Matrix Analysis and Applications 32 (4), 1513-1523, 2011
132011
Probabilistic performance profiles for the experimental evaluation of stochastic algorithms
A Barreto, HS Bernardino, HJC Barbosa
Proceedings of the 12th annual conference on Genetic and evolutionary …, 2010
132010
On-line reinforcement learning using incremental kernel-based stochastic factorization
D Precup, J Pineau, AS Barreto
Advances in Neural Information Processing Systems, 1484-1492, 2012
122012
Value-aware loss function for model-based reinforcement learning
A Farahmand, A Barreto, D Nikovski
Artificial Intelligence and Statistics, 1486-1494, 2017
112017
Analysis of composition-based metagenomic classification
S Higashi, AMS Barreto, ME Cantão, ATR de Vasconcelos
BMC genomics 13 (5), S1, 2012
102012
Universal successor features approximators
D Borsa, A Barreto, J Quan, D Mankowitz, R Munos, H van Hasselt, ...
arXiv preprint arXiv:1812.07626, 2018
82018
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