Representation of Empirically Derived Causal Relationships

Robert L. Blum
1983 International Joint Conference on Artificial Intelligence  
The objective of this paper is to present a method for the computer representation of empirically derived causal relationships (CR's). This method draws on the theory of multivariate linear models and path analysis. The method is contrasted with the predicate calculus based methods used by most researchers in artificial intelligence. The representation presented here has been used to store information on medical CR's derived empirically from a large clinical database by a computer program
more » ... RX. The principal emphasis in the representation is on capturing the intensities and variances of effects and the variation in the effects across a patient population. Once incorporated into RX's knowledge base, this information is subsequently used by RX in determining the validity of other CR's. The representation uses a directed graph formalism in which the nodes are frames and the arcs contain seven descriptive features of individual CR'
dblp:conf/ijcai/Blum83 fatcat:fnkpezrwbrdlhjsprjgpltm3ry