AAAI Publications, Workshops at the Twenty-Fourth AAAI Conference on Artificial Intelligence

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Formulating Template Consistency in Inductive Logic Programming as a Constraint Satisfaction Problem
Roman Bartak, Ondrej Kuzelka, Filip Zelezny

Last modified: 2010-07-07

Abstract


Inductive Logic Programming (ILP) deals with the problem of finding a hypothesis covering positive examples and excluding negative examples, where both hypotheses and examples are expressed in first-order logic. In this paper we employ constraint satisfaction techniques to model and solve a problem known as template ILP consistency, which assumes that the structure of a hypothesis is known and the task is to find a unification of the contained variables such that no negative example is subsumed by the hypothesis and all positive examples are subsumed.

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