Learning Higher-Order Programs through Predicate Invention

Authors

  • Andrew Cropper University of Oxford
  • Rolf Morel University of Oxford
  • Stephen H. Muggleton Imperial College London

DOI:

https://doi.org/10.1609/aaai.v34i09.7113

Abstract

A key feature of inductive logic programming (ILP) is its ability to learn first-order programs, which are intrinsically more expressive than propositional programs. In this paper, we introduce ILP techniques to learn higher-order programs. We implement our idea in Metagolho, an ILP system which can learn higher-order programs with higher-order predicate invention. Our experiments show that, compared to first-order programs, learning higher-order programs can significantly improve predictive accuracies and reduce learning times.

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Published

2020-04-03

How to Cite

Cropper, A., Morel, R., & Muggleton, S. H. (2020). Learning Higher-Order Programs through Predicate Invention. Proceedings of the AAAI Conference on Artificial Intelligence, 34(09), 13655-13658. https://doi.org/10.1609/aaai.v34i09.7113