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 unification of the contained variables. In particular, we present a constraint model with index variables accompanied by a Boolean model to strengthen inference and hence improve efficiency. The efficiency of models is demonstrated experimentally.
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Barták, R., Černoch, R., Kuželka, O. et al. Formulating the template ILP consistency problem as a constraint satisfaction problem. Constraints 18, 144–165 (2013). https://doi.org/10.1007/s10601-013-9141-7
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DOI: https://doi.org/10.1007/s10601-013-9141-7