Abstract
A major question asked by learning in the limit from positive data is about what classes of languages are learnable with respect to a given learning criterion. We are particularly interested in the reasons for a class of languages to be unlearnable. We consider two types of reasons. One type is called topological (as an example, Gold has shown that no class containing an infinite language and all its finite sub-languages is learnable). Another reason is called computational (as the learners are required to be algorithmic). In particular, two learning criteria might allow for learning different classes of languages because of different topological restrictions, or because of different computational restrictions.
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