Induction Learning Based on Specific Objects

Haoran Wang, Tianming Gui, Qinzhou Niu
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Abstract

This paper proposes a new induction learning method based on the specific object, which allows the learning of the specific object in answer set programming (ASP), which is helpful to the research of inductive logic learning. The framework is composed of background knowledge , learning object (OBJECT), hypothesis space (Sm) and hypothesis (H). This kind of programming method which obtains hypothesis through background knowledge learning is called inductive logic programming.
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基于特定对象的归纳学习
本文提出了一种新的基于特定对象的归纳学习方法,该方法允许在回答集规划(ASP)中对特定对象进行学习,有助于归纳逻辑学习的研究。该框架由背景知识、学习对象(object)、假设空间(Sm)和假设(H)组成。这种通过背景知识学习获得假设的编程方法称为归纳逻辑编程。
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