889 search results - page 56 / 178 » Observational Learning in Random Networks |
132
Voted
ALGOSENSORS
2009
Springer
15 years 9 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...
123
Voted
UAI
2003
15 years 3 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...
126
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IJAR
2010
15 years 1 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...
116
Voted
ICRA
2009
IEEE
15 years 9 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 ...
115
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AIPS
2009
15 years 3 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...