Abstract
Inductive learning is an important subject in artificial intelligence. As a concern of theoretical computer science, this paper investigates the complexity of induction of structural descriptions which is fundamental to inductive learning. The general complexity is derived, and a way of approaching the induction, namely, computing the maximal common generalizations by pairing, is also presented with its inherent complexity. A group ofNP-complete andNP-hard problems are introduced when showing the complexities.
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