Brian John Cragun

A decision-table-used processor for checking completeness and consistency in rule-based expert systems

Abstract This paper addresses the issues of completeness and consistency in rule-based expert systems. The approach presented uses decision tables, which have a close relationship to rule-based knowledge bases. A decision-table-supported processor is described which checks knowledge bases for completeness and consistency using this approach. It creates a large decision table from the rules of the knowledge base, splits the decision table into subtables with similar logic, checks each subtable for completeness and consistency, and reports any missing rules. This method is faster than enumeration only methods of checking completeness, and provides implicit context determination of production rules.