Learning recursive languages from good examples

Authors: Steffen Lange, Jochen Nessel and Rolf Wiehagen.
Email: slange@informatik.uni-leipzig.de

Source: Annals of Mathematics and Artificial Intelligence Vol. 23, No. 1-2, 1998, 27-52.

Abstract. We study learning of indexable families of recursive languages from good examples. We show that this approach can be considerably more powerful than learning from all examples and point out reasons for this additional power. We present several characterizations of types of learning from good examples. We derive similarities as well as differences to learning of recursive functions from good examples.

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