Abstract
Concept learning systems have a great deal to gain by showing
more initiative; in particular, by actively posing test examples rather
than passively waiting for more examples to appear. This paper briefly
reviews different approaches to selecting examples, and goes on to
explore the ramifications of one in detail. Current implementations
are overly simplistic because they assume a hierarchically-structured
network of concepts. It is shown how they break down in more general
partially-ordered domains, and a new method which copes with this
situation is described and illustrated. Finally, the
techniques are related to the version-space approach to provide them
with a well-understood theoretical underpinning.
Notes
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