Extensions of Dynamic Programming as a New Tool for Rough Sets

We consider extensions of Dynamic Programming which can work with problems containing exponential number of subproblems, and allow sequential optimization relative to different criteria and inference of relationships among these criteria. We use these extensions to study and optimize exact and approximate decision trees and rules.