IJAR
2006
13 years 4 months ago
2006
IJAR
2006
13 years 4 months ago
2006
We describe a new graphical language for specifying asymmetric decision problems. The language is based on a filtered merge of several existing languages including sequential valu...
IJAR
2006
13 years 4 months ago
2006
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
IJAR
2006
13 years 4 months ago
2006
We consider the problem of learning the parameters of a Bayesian network from data, while taking into account prior knowledge about the signs of influences between variables. Such...
IJAR
2006
13 years 4 months ago
2006
In spatial reasoning, in particular for applications in image understanding, structure recognition and computer vision, a lot of attention has to be paid to spatial relationships ...
IJAR
2006
13 years 4 months ago
2006
An important class of continuous Bayesian networks are those that have linear conditionally deterministic variables (a variable that is a linear deterministic function of its pare...
IJAR
2006
13 years 4 months ago
2006
Mixtures of truncated exponentials (MTE) potentials are an alternative to discretization for solving hybrid Bayesian networks. Any probability density function can be approximated...
IJAR
2006
13 years 4 months ago
2006
IJAR
2006
13 years 4 months ago
2006
We describe in this paper a system for exact inference with relational Bayesian networks as defined in the publicly available Primula tool. The system is based on compiling propos...
IJAR
2006
13 years 4 months ago
2006
Although influence diagrams are powerful tools for representing and solving complex decisionmaking problems, their evaluation may require an enormous computational effort and this...