Can complexity theory benefit from learning theory?

Abstract

We show that the results achieved within the framework of Computational Learning Theory are relevant enough to have non-trivial applications in other areas of Computer Science, namely in Complexity Theory. Using known results on efficient query-learnability of some Boolean concept classes, we prove several (co-NP-completeness) results on the complexity of certain decision problems concerning representability of general Boolean functions in special forms.