Andre Barreto
Andre Barreto
Research Scientist, Google DeepMind
Verified email at
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
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
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
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
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
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
Reinforcement learning using kernel-based stochastic factorization
AS Barreto, D Precup, J Pineau
Advances in Neural Information Processing Systems, 720-728, 2011
GOLS—genetic orthogonal least squares algorithm for training RBF networks
AMS Barreto, HJC Barbosa, NFF Ebecken
Neurocomputing 69 (16-18), 2041-2064, 2006
Graph layout using a genetic algorithm
AMS Barreto, HJC Barbosa
Proceedings. Vol. 1. Sixth Brazilian Symposium on Neural Networks, 179-184, 2000
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
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
Practical kernel-based reinforcement learning
A Barreto, D Precup, J Pineau
The Journal of Machine Learning Research 17 (1), 2372-2441, 2016
Policy iteration based on stochastic factorization
AMS Barreto, J Pineau, D Precup
Journal of Artificial Intelligence Research 50, 763-803, 2014
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
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
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
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
Value-aware loss function for model-based reinforcement learning
A Farahmand, A Barreto, D Nikovski
Artificial Intelligence and Statistics, 1486-1494, 2017
Analysis of composition-based metagenomic classification
S Higashi, AMS Barreto, ME Cantão, ATR de Vasconcelos
BMC genomics 13 (5), S1, 2012
Alternative evolutionary algorithms for evolving programs: evolution strategies and steady state gp
D Whitley, M Richards, R Beveridge, A da Motta Salles Barreto
Proceedings of the 8th annual conference on Genetic and evolutionary …, 2006
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