71 search results - page 2 / 15 » A Causal Bayesian Network View of Reinforcement Learning |
ICML
2008
IEEE
15 years 10 months ago
2008
IEEE
We present an algorithm, HI-MAT (Hierarchy Induction via Models And Trajectories), that discovers MAXQ task hierarchies by applying dynamic Bayesian network models to a successful...
ECML
2006
Springer
15 years 1 months ago
2006
Springer
Causal independence modelling is a well-known method both for reducing the size of probability tables and for explaining the underlying mechanisms in Bayesian networks. In this pap...
AAAI
2008
14 years 12 months ago
2008
Modern Bayesian Network learning algorithms are timeefficient, scalable and produce high-quality models; these algorithms feature prominently in decision support model development...
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METMBS
2003
14 years 11 months ago
2003
Causal Probabilistic Networks (CPNs), (a.k.a. Bayesian Networks, or Belief Networks) are well-established representations in biomedical applications such as decision support system...
AIME
2009
Springer
15 years 4 months ago
2009
Springer
Abstract. Mammographic analysis is a difficult task due to the complexity of image interpretation. This results in diagnostic uncertainty, thus provoking the need for assistance by...