Combining Models of Approximation with Partial Learning

5 Jul 2015Ziyuan GaoFrank StephanSandra Zilles

In Gold's framework of inductive inference, the model of partial learning requires the learner to output exactly one correct index for the target object and only the target object infinitely often. Since infinitely many of the learner's hypotheses may be incorrect, it is not obvious whether a partial learner can be modifed to "approximate" the target object... (read more)

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