10.4230/LIPICS.ICLP.2010.281
Pahlavi, Niels
Niels
Pahlavi
Higher-order Logic Learning and lambda-Progol
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
2010
Article
Inductive Logic Programming
Progol
Higher-order Logic
Higher-order Logic Learning
$lambda$Prolog
Hermenegildo, Manuel
Manuel
Hermenegildo
Schaub, Torsten
Torsten
Schaub
2010
2010-06-25
2010-06-25
2010-06-25
en
urn:nbn:de:0030-drops-26098
10.4230/LIPIcs.ICLP.2010
978-3-939897-17-0
1868-8969
10.4230/LIPIcs.ICLP.2010
LIPIcs, Volume 7, ICLP 2010
Technical Communications of the 26th International Conference on Logic Programming
2013
7
35
281
285
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Hermenegildo, Manuel
Manuel
Hermenegildo
Schaub, Torsten
Torsten
Schaub
1868-8969
Leibniz International Proceedings in Informatics (LIPIcs)
2010
7
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
5 pages
349428 bytes
application/pdf
Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported license
info:eu-repo/semantics/openAccess
We present our research produced about Higher-order Logic Learning (HOLL), which consists of adapting First-order Logic Learning (FOLL), like Inductive Logic Programming (ILP), within a Higher-order Logic (HOL) context. We describe a first working implementation of lambda-Progol, a HOLL system adapting the ILP system Progol and the HOL formalism lambda-Prolog. We compare lambda-Progol and Progol on the learning of recursive theories showing that HOLL can, in these cases, outperform FOLL.
LIPIcs, Vol. 7, Technical Communications of the 26th International Conference on Logic Programming, pages 281-285