Evolution of expert systems

Expert systems are computer programs for providing expertise emulative of that which might be expected from human experts in solving complex problems for which analytical solutions are not available. Evolution of an expert system refers to the initial development of the system and its continuing modification in order to improve its performance. Any modifications made to an expert system have the potential of producing undesirable logical errors and side-effects that are difficult to find or prevent. Although much research has focused on facilitating the evolution of expert systems, most of the limitations still exist.

This dissertation proposes an approach for structuring and evolving expert systems for applications in which the provision of the desired expertise is beyond the reach of either analytical or traditional heuristic approaches, but in which the knowledge domain is causally connected and the relevant causality can be expressed in procedural form.

The research vehicle used is that of a hypothetical manufacturing system in which products of different types use some of the same workstations, and some of the product types loop back to workstations that they have previously used. The expertise sought is that of scheduling starts of products into the first stage of production so as to yield a stream of output that satisfies a user-specified balance among a variety of business performance measures including timeliness of production output.