Inductive logic programming at 30

Abstract Inductive logic programming (ILP) is a form of logic-based machine learning. The goal to induce hypothesis (a program) that generalises given training examples and background knowledge. As ILP turns 30, we review the last decade research. We focus on (i) new meta-level search methods, (ii) techniques for learning recursive programs, (iii) approaches predicate invention, (iv) use different technologies. conclude by discussing current limitations directions future