Fundamental concepts of qualitative probabilistic networks

摘要

Graphical representations for probabilistic relationships have recently received considerable attention in AI. Qualitative probabilistic networks abstract from the usual numeric representations by encoding only qualitative relationships, which are inequality constraints on the joint probability distribution over the variables. Although these constraints are insufficient to determine probabilities uniquely, they are designed to justify the deduction of a class of relative likelihood conclusions that imply useful decision-making properties.