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ECML
2005
Springer
14 years 4 months ago
Active Learning in Partially Observable Markov Decision Processes
This paper examines the problem of finding an optimal policy for a Partially Observable Markov Decision Process (POMDP) when the model is not known or is only poorly specified. W...
Robin Jaulmes, Joelle Pineau, Doina Precup
IJCNN
2000
IEEE
14 years 3 months ago
An Incremental Growing Neural Network and its Application to Robot Control
This paper describes a novel network model, which is able to control its growth on the basis of the approximation requests. Two classes of self-tuning neural models are considered...
A. Carlevarino, R. Martinotti, Giorgio Metta, Giul...
ICANN
2007
Springer
14 years 2 months ago
The Role of Internal Oscillators for the One-Shot Learning of Complex Temporal Sequences
We present an artificial neural network used to learn online complex temporal sequences of gestures to a robot. The system is based on a simple temporal sequences learning architec...
Matthieu Lagarde, Pierre Andry, Philippe Gaussier
CORR
2011
Springer
213views Education» more  CORR 2011»
13 years 5 months ago
Adapting to Non-stationarity with Growing Expert Ensembles
Forecasting sequences by expert ensembles generally assumes stationary or near-stationary processes; however, in complex systems and many real-world applications, we are frequentl...
Cosma Rohilla Shalizi, Abigail Z. Jacobs, Aaron Cl...
CVPR
2008
IEEE
15 years 24 days ago
Shading models for illumination and reflectance invariant shape detectors
Many objects have smooth surfaces of a fairly uniform color, thereby exhibiting shading patterns that reveal information about its shape, an important clue to the nature of the ob...
Peter Nillius, Josephine Sullivan, Antonis A. Argy...