Causal Ordering in a Mixed Structure

Abstract

This paper describes a computational approach, based on the theory ofcausal ordering, for inferring causality from an acausal, formal description of a phenomena. Causal ordering is an asymmetric relation among the variables in a self-contained equilibrium and dynamic structure, which seems to reflect people's intuitive notion of causal dependency relations among variables in a system. This paper extends the theory to cover models consisting of mixture ofdynamic and equilibrium equations. When people's intuitive causal understanding ofasituation isbased on a mixed description, the causal ordering produced by the extension reflects this intuititve understanding better than that ofan equilibrium description. The paper also discusses the view ofa mixed model asan approximation to acompletely dynamic model.