A Knowledge-based Decision Support System for Mining Method Selection for Ore Deposits

In recent years, research in the field of artificial intelligence (AI) has had many important successes. Among the most significant of these has been the development of powerful new computer software known as the "expert systems". Expert system programs designed to provide expert-level consultative advice in mineral exploration (Duda et al, 1981), scientific (Feigenbaum, Buchanan and Lederburg, 1971) and medical (Shortliffe, 1976) problem solving are generally acknowledged to be among the forerunners of this research. As the decision makers virtually in all fields face a more complex and involved world within which to operate, the need for some decision support is also becoming urgent. Thus applications of expert systems continue to spread out reaching problems that, because of their dimensions or particular aspects, set more demand on the decision methodologies. To meet these new requirements, many activities which were performed in the past by the domain expert or engineer must become automated. Furthermore, previous research (Dawes and Corrigan, 1974; Dawes, 1979) has shown that automating an expert's decision rules often provide better decision than the expert does. For large systems it would be very useful (or even necessary) to have formal tools, allowing one for example, to automatically discover inconsistencies, contradictions or redundancies, or to identify the possibilities of wrong lines of reasoning in the decision process.