Learning higher-order logic programs

A key feature of inductive logic programming is its ability to learn first-order programs, which are intrinsically more expressive than propositional programs. In this paper, we introduce techniques to learn higher-order programs. Specifically, we extend meta-interpretive learning (MIL) to support l...

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Veröffentlicht in:	Machine learning Jg. 109; H. 7; S. 1289 - 1322
Hauptverfasser:	Cropper, Andrew, Morel, Rolf, Muggleton, Stephen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.07.2020 Springer Nature B.V
Schlagworte:	Artificial Intelligence Complexity Computer Science Control Encryption Learning Logic programming Logic programs Machine Learning Mechatronics Natural Language Processing (NLP) Prolog Robotics Simulation and Modeling Special Issue of the Inductive Logic Programming (ILP) 2019
ISSN:	0885-6125, 1573-0565
Online-Zugang:	Volltext
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