Qualitative Simulation as Causal Explanation

Abstract
To give a causal explanation of an event is to show how that event could be deduced from a set of universal laws and a set of initial conditions. How can this philosophical definition be related to the diagnostic causal explanations of a practicing expert? An expert physician gives a causal explanation of a disease state by referring to knowledge of the structure of the physiological mechanisms involved (the laws) and to the environment that the mechanism is exposed to (the initial state). The expert's knowledge, however, is qualitative and is thus able to express incomplete knowledge about the exact structure of the mechanism or the precise state of the patient. A qualitative representation for the structure of a mechanism, as well as the QSIM algorithm for deriving qualitative behavioral predictions from that structure and an initial state, are described. Looking in detail at the mechanism whereby the kidney maintains the body's water balance, qualitative predictions are demonstrated of 1) the response of the normal mechanism to a change in its environment, 2) the response of the diseased mechanism to the normal environment, and 3) the response of the diseased mechanism to therapy. To extend these methods to more complex problems, methods are required to abstract a complex mechanism into a hierarchy of simpler models. An abstraction relation based on relative time scales is presented which allows one equilibrium process in a complex system to view faster processes as instantaneous and slower processes as constant.

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