Learning Higher-Order Programs through Predicate Invention
| Autor: | Stephen Muggleton, Rolf Morel, Andrew Cropper |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Programming language
Computer science 02 engineering and technology General Medicine Predicate (mathematical logic) computer.software_genre Inductive logic programming Order (business) 020204 information systems 0202 electrical engineering electronic engineering information engineering Key (cryptography) Feature (machine learning) 020201 artificial intelligence & image processing computer |
| Zdroj: | AAAI |
| ISSN: | 2374-3468 2159-5399 |
| DOI: | 10.1609/aaai.v34i09.7113 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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