ABSTRACT Prospector is a computer consultant system intended to aid geologists in evaluating the favorability of an exploration site or region for occurrences of ore deposits of particular types. Knowledge about a particular type of ore deposit is encoded in a computational model representing observable geological features and the relative significance thereof. We describe the form of models in Prospector, focussing on inference networks of geological assertions and the Bayesian propagation formalism used to represent the judgmental reasoning process of the economic geologist who serves as model designer. Following the initial design of a model, simple performance evaluation techniques are used to assess the extent to which the performance of the model reflects faithfully the intent of the model designer. These results identify specific portions of the model that might benefit from "fine tuning", and establish priorities for such revisions. This description of the Prospector system and the model design process serves to illustrate the process of transferring human expertise about a subjective domain into a mechanical realization. I. INTRODUCTION In an increasingly complex and specialized world, human expertise about diverse subjects spanning scientific, economic, social, and political issues plays an increasingly important role in the functioning of all kinds of organizations. Although computers have become indispensable tools in many endeavors, we continue to rely heavily on the human expert's ability to identify and synthesize diverse factors, to form judgments, evaluate alternatives, and make decisions -- in sum, to apply his or her years of experience to the problem at hand. This is especially valid with regard to domains that are not easily amenable to precise scientific formulations, i.e., to domains in which experience and subjective judgment plays a major role.

This paper describes an evaluation and several applications of a knowledge-based system, the PROSPECTOR consultant for mineral exploration. PROSPECTOR is a rule-based judgmental reasoning system that evaluates the mineral potential of a site or region with respect to inference network models of specific classes of ore deposits. Knowledge about a particular type of ore deposit is encoded in a computational model representing observable geological features and the relative significance thereof.

We expect that the percentage of DNA which codes for heuristics rather than proteins would increase with the complexity and sophistication of the organism. Man should have more heuristics than chickens, which should have more than E. coll. This isn't because we're "better", just because our DNA program is longer and more involved; if our ability to adapt is to be anywhere near as good as bacteria's, we must compensate for our unwieldy program size and generation time by employing poweful judgmental rules, heuristics which put each generation to maximum use.