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Weighted Decision Tables An Alternative Solution for Ambiguity
ITT Advanced Technology Center, Shelton, USA
Ambiguity in decision tables reduces or eliminates their effectiveness as a control structure in programming languages or as a representation of production rules in an expert system. Rather than expand the table to remove the ambiguity, three weighting schemes for the condition stub are proposed. Rule weights explicitly assign a rule precedence by assigning a weight to each rule. Condition weights implicitly define precedence by weighting each condition. Entry-weighted tables assign precedence by assigning each entry a weight. In all cases, ambiguity is eliminated by the assignment or calculation of unique rule weights within each ambiguous set. The use of weighted decision tables, in addition to improving the programming language interface, provides improved documentation for complex situations.