Olivier Sigaud
Olivier Sigaud
professeur d'informatique, Sorbonne Université
Adresse e-mail validée de upmc.fr - Page d'accueil
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Markov decision processes in artificial intelligence
John Wiley & Sons, 2010
235*2010
Path integral policy improvement with covariance matrix adaptation
F Stulp, O Sigaud
arXiv preprint arXiv:1206.4621, 2012
2062012
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
158*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
1412006
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
1382011
Learning classifier systems: a survey
O Sigaud, SW Wilson
Soft Computing 11 (11), 1065-1078, 2007
1302007
Robot skill learning: From reinforcement learning to evolution strategies
F Stulp, O Sigaud
Paladyn, Journal of Behavioral Robotics 4 (1), 49-61, 2013
1232013
Anticipatory behavior in adaptive learning systems: Foundations, Theories and Systems
MV Butz, O Sigaud, P Gérard
Lecture Notes in Artificial Intelligence,, 2003
1172003
Many regression algorithms, one unified model: A review
F Stulp, O Sigaud
Neural Networks 69, 60-79, 2015
1122015
Internal models and anticipations in adaptive learning systems
MV Butz, O Sigaud, P Gerard
Anticipatory behavior in adaptive learning systems, 86-109, 2003
1122003
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
1012003
GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms
C Colas, O Sigaud, PY Oudeyer
International Conference in Machine Learning (ICML), 2018
842018
Learning Compact Parameterized Skills with a Single Regression
F Stulp, G Raiola, A Hoarau, S Ivaldi, O Sigaud
IEEE Humanoids 5, 9, 2013
832013
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 Comput Biol 10 (2), e1003466, 2014
822014
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
792014
CURIOUS: intrinsically motivated modular multi-goal reinforcement learning
C Colas, P Fournier, M Chetouani, O Sigaud, PY Oudeyer
International conference on machine learning, 1331-1340, 2019
70*2019
Policy improvement methods: Between black-box optimization and episodic reinforcement learning
F Stulp, O Sigaud
682012
Deep unsupervised network for multimodal perception, representation and classification
A Droniou, S Ivaldi, O Sigaud
Robotics and Autonomous Systems 71, 83-98, 2015
602015
YACS: a new learning classifier system using anticipation
P Gerard, W Stolzmann, O Sigaud
Soft Computing 6 (3-4), 216-228, 2002
542002
Towards deep developmental learning
O Sigaud, A Droniou
IEEE Transactions on Cognitive and Developmental Systems 8 (2), 99-114, 2016
492016
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