889 search results - page 56 / 178 » Observational Learning in Random Networks |
ALGOSENSORS
2009
Springer
14 years 3 months ago
2009
Springer
We introduce a framework for storing and processing kinetic data observed by sensor networks. These sensor networks generate vast quantities of data, which motivates a significant...
UAI
2003
13 years 10 months ago
2003
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...
IJAR
2010
13 years 7 months ago
2010
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
ICRA
2009
IEEE
14 years 4 months ago
2009
IEEE
— In this paper, we present an approach that allows a robot to observe, generalize, and reproduce tasks observed from multiple demonstrations. Motion capture data is recorded in ...
AIPS
2009
13 years 10 months ago
2009
It has long been recognized that users can have complex preferences on plans. Non-intrusive learning of such preferences by observing the plans executed by the user is an attracti...