Learning recursive languages from good examples

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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