Olivier Sigaud
Olivier Sigaud
professeur d'informatique, Sorbonne Université
確認したメール アドレス: upmc.fr - ホームページ
タイトル引用先
Markov decision processes in artificial intelligence
John Wiley & Sons, 2010
156*2010
Path integral policy improvement with covariance matrix adaptation
F Stulp, O Sigaud
arXiv preprint arXiv:1206.4621, 2012
1542012
Anticipatory behavior in adaptive learning systems: From brains to individual and social behavior
MV Butz, O Sigaud, G Pezzulo, G Baldassarre
Lecture Notes In Artificial Intelligence, Springer, 2007
148*2007
Learning the structure of factored markov decision processes in reinforcement learning problems
T Degris, O Sigaud, PH Wuillemin
Proceedings of the 23rd international conference on Machine learning, 257-264, 2006
1262006
On-line regression algorithms for learning mechanical models of robots: a survey
O Sigaud, C Salaün, V Padois
Robotics and Autonomous Systems 59 (12), 1115-1129, 2011
1132011
Learning classifier systems: a survey
O Sigaud, SW Wilson
Soft Computing 11 (11), 1065-1078, 2007
1132007
Internal models and anticipations in adaptive learning systems
MV Butz, O Sigaud, P Gerard
Anticipatory behavior in adaptive learning systems, 86-109, 2003
1042003
Robot skill learning: From reinforcement learning to evolution strategies
F Stulp, O Sigaud
Paladyn, Journal of Behavioral Robotics 4 (1), 49-61, 2013
862013
Anticipatory behavior: Exploiting knowledge about the future to improve current behavior
MV Butz, O Sigaud, P Gérard
Anticipatory behavior in adaptive learning systems, 1-10, 2003
862003
Anticipatory behavior in adaptive learning systems: Foundations, Theories and Systems
MV Butz, O Sigaud, P Gérard
Lecture Notes in Artificial Intelligence,, 2003
762003
Object learning through active exploration
S Ivaldi, SM Nguyen, N Lyubova, A Droniou, V Padois, D Filliat, ...
IEEE Transactions on Autonomous Mental Development 6 (1), 56-72, 2014
672014
Many regression algorithms, one unified model: A review
F Stulp, O Sigaud
Neural Networks 69, 60-79, 2015
632015
Modelling individual differences in the form of Pavlovian conditioned approach responses: a dual learning systems approach with factored representations
F Lesaint, O Sigaud, SB Flagel, TE Robinson, M Khamassi
PLoS computational biology 10 (2), e1003466, 2014
622014
Learning Compact Parameterized Skills with a Single Regression
F Stulp, G Raiola, A Hoarau, S Ivaldi, O Sigaud
IEEE Humanoids 5, 9, 2013
622013
Policy improvement methods: Between black-box optimization and episodic reinforcement learning
F Stulp, O Sigaud
522012
YACS: a new learning classifier system using anticipation
P Gerard, W Stolzmann, O Sigaud
Soft Computing 6 (3-4), 216-228, 2002
502002
YACS: Combining Anticipation and Dynamic Programming in Classifier Systems
P Gérard, O Sigaud
LNAI 1996: Advances in Classifier Systems, 52-69, 2003
39*2003
Combining Latent Learning with Dynamic Programming in the Modular Anticipatory Classifier System
P Gérard, J Meyer, O Sigaud
European Journal of Operational Research, 2005
382005
Deep unsupervised network for multimodal perception, representation and classification
A Droniou, S Ivaldi, O Sigaud
Robotics and Autonomous Systems 71, 83-98, 2015
372015
Gated autoencoders with tied input weights
A Droniou, O Sigaud
Proceedings of The 30th International Conference on Machine Learning, 154-162, 2013
352013
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