Practical machine intelligence

In every professional field there are large bodies of information acquired through study and experience by practitioners. In many fields, individuals can be identified whose performance consistently approaches the best. The goal of expert systems technology is to embody the experts' knowledge in some field within a computer. Then, the computer can act as an expert consultant for non-expert professionals or laymen. Existing systems, such as MYCIN [2], for diagnosing blood infections, or PROSPECTOR [3], for evaluating field sites for minable mineral deposits, can perform at a level exceeding that of the average practitioner in the field. These systems typically run on large, time-shared computers. There are two components to an expert system: the expert knowledge itself, and a'core' system for manipulating that knowledge and interacting with the user. General methodologies have been developed for encoding expert knowledge; the encoding is typically done by a computer scientist in close collaboration with an expert or experts from the field of specialization.