152 search results - page 10 / 31 » Observational learning in an uncertain world |
PRL
2011
13 years 2 months ago
2011
In some real world applications, such as spectrometry, functional models achieve better predictive performances if they work on the derivatives of order m of their inputs rather t...
ECML
2005
Springer
14 years 28 days ago
2005
Springer
Abstract. Learning to act in an unknown partially observable domain is a difficult variant of the reinforcement learning paradigm. Research in the area has focused on model-free m...
IPSN
2003
Springer
14 years 17 days ago
2003
Springer
Abstract. The issue of data association arises frequently in sensor networks; whenever multiple sensors and sources are present, it may be necessary to determine which observations...
IOR
2010
13 years 5 months ago
2010
We study a problem of dynamic pricing faced by a vendor with limited inventory, uncertain about demand, aiming to maximize expected discounted revenue over an infinite time horiz...
ATAL
2010
Springer
13 years 8 months ago
2010
Springer
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...