Modelling with Context-Dependent Causality

Decision support systems may require the use of existing complex mathematical models. It is desirable to reduce the equations of such a model to an explanatory causal form to support decision making. It is argued here that a combination of extracting information from the user and heuristics to reduce the equations to a suitable form are sufficient to produce a reasonable causal explanation from equations. The method identifies causality in a physical system with or without feedback. The method also allows consistency checking between equations and user generated causal reasoning. This method has been implemented in Hypercard on a Macintosh to provide an accessible graphically oriented decision support tool.