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Refuting Learning Revisited

机译:重新学习反驳

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We consider, within the framework of inductive inference, the concept of refuting learning as introduced by Mukouchi and Arikawa, where the learner is not only required to learn all concepts in a given class but also has to explicitly refute concepts outside the class. In the first part of the paper, we consider learning from text and introduce a concept of limit-refuting learning that is intermediate between refuting learning and reliable learning. We give characterizations for these concepts and show some results about their relative strength and their relation to confident learning. In the second part of the paper we consider learning from texts that for some k contain all positive II_k-formulae that are valid in the standard structure determined by the set to be learned. In this model, the following results can be shown. For the language with successor, any countable axiomatizable class can be limit-refuting learned from II_1-texts. For the language with successor and order, any countable axiomatizable class can be reliably learned from II_1-texts and can be limit-refuting learned from II_2-texts, whereas the axiomatizable class of all finite sets cannot be limit-refuting learned from II_1-texts. For the full language of arithmetic, which contains in addition plus and times, for any k there is an axiomatizable class that can be limit-refuting learned from II_(k+1)-texts but not from II_k-texts. A similar result with k + 3 in place of k + 1 holds with respect to the language of Presburger's arithmetic.
机译:我们认为,在归纳推理的框架内,是Mukouchi和Arikawa提出的反驳学习的概念,学习者不仅需要学习给定班级中的所有概念,而且还必须明确反驳课外的概念。在本文的第一部分中,我们考虑从文本中学习,并引入了极限反驳学习的概念,该概念介于反驳学习和可靠学习之间。我们对这些概念进行了表征,并给出了有关它们的相对强度及其与自信学习的关系的一些结果。在本文的第二部分中,我们考虑从文本中学习,对于某些k而言,它包含在要学习的集合所确定的标准结构中有效的所有正II_k公式。在此模型中,可以显示以下结果。对于具有后继语言的语言,可以从II_1文本中学习任何可计数的可公化类。对于具有后继和顺序的语言,可以从II_1文本可靠地学习任何可数的可公理化类,并且可以从II_2文本进行极限反驳的学习,而所有有限集的可公理化的类不能从II_1文本学来极限反驳。 。对于完整的算术语言(包含加号和时间),对于任何k,都有一个可公理化的类,可以从II_(k + 1)个文本(而非II_k个文本)中学习极限极限。就普雷斯堡算法的语言而言,用k + 3代替k +1的结果相似。

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