Bi-criteria Optimization Problem for Rules and Systems of Rules: Cost Versus Uncertainty (Completeness)

Abstract

In this chapter, we consider algorithms which construct the sets of Pareto optimal points for bi-criteria optimization problems for decision (inhibitory) rules and rule systems relative to a cost function and an uncertainty (completeness) measure. We show how the constructed set of Pareto optimal points can be transformed into the graphs of functions which describe the relationships between the considered cost function and uncertainty (completeness) measure. Computer experiments provide us with examples of trade-off between complexity and accuracy for decision and inhibitory rule systems.