Bounds on Complexity and Algorithms for Construction of Nondeterministic and Strongly Nondeterministic Decision Trees for Decision Tables

Abstract

In this chapter, we consider bounds on the minimum complexity, an approach to proof of lower bounds, and algorithms for construction of nondeterministic and strongly nondeterministic decision trees. The bounds on complexity are true for arbitrary complexity functions. The approach to proof of lower bounds assumes that the complexity functions have the property \(\varLambda 2\). The considered algorithms require complexity functions having properties \(\varLambda 1\), \(\varLambda 2\), and \(\varLambda 3\).