Refereed full papers (journals, book chapters, international conferences)

1988

@inproceedings{VeP1988,
	vgclass =	{refpap},
	author =	{Thomas Verma and Judea Pearl},
	title =	{Causal Networks: Semantics and Expressiveness},
	booktitle =	{Uncertainty in Artificial Intelligence--4},
	address =	{New York, NY, USA},
	pages =	{69--76},
	publisher =	{Elsevier Science Publishing Company, Inc.},
	year =	{1988},
	url =	{http://www2.sis.pitt.edu/\~{}dsl/UAI/UAI88/Verma.UAI88.html},
	abstract =	{Dependency knowledge of the form "x is independent of y
	once z is known" invariably obeys the four graphoid axioms, examples
	include probabilistic and database dependencies. Often, such knowledge
	can be represented efficiently with graphical structures such as
	undirected graphs and directed acyclic graphs (DAGs). In this paper we
	show that the graphical criterion called d-separation is a sound rule
	for reading independencies from any DAG based on a causal input list
	drawn from a graphoid. The rule may be extended to cover DAGs that
	represent functional dependencies as well as conditional
	dependencies.},
}