Inductive logic programming at 30: a new introduction. (English) Zbl 07565999
Summary: Inductive logic programming (ILP) is a form of machine learning. The goal of ILP is to induce a hypothesis (a set of logical rules) that generalises training examples. As ILP turns 30, we provide a new introduction to the field. We introduce the necessary logical notation and the main learning settings; describe the building blocks of an ILP system; compare several systems on several dimensions; describe four systems (Aleph, TILDE, ASPAL, and Metagol); highlight key application areas; and, finally, summarise current limitations and directions for future research.
Keywords:
inductive logic programmingReferences:
[1] | Springer. |
[2] | Revised Papers, Vol. 5989 ofLecture Notes in Computer Science, pp. 131-148. Springer. |
[3] | ijcai.org. |
[4] | Springer |
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