The primary goal of this paper is to introduce the potential of artifi
cial intelligence (AI) methods to researchers in sleep classification.
AI provides learning procedures for the construction of a sleep class
ifier, prescribing how to combine the observed parameters and how to d
erive the corresponding decision thresholds. A case study reporting a
successful application of an automatic induction of decision trees and
of a learning vector quantizer to this domain is presented.