Inductive logic programming at 30 [article]

Andrew Cropper, Sebastijan Dumančić, Richard Evans, Stephen H. Muggleton
2021 arXiv   pre-print
Inductive logic programming (ILP) is a form of logic-based machine learning. The goal is to induce a hypothesis (a logic program) that generalises given training examples. As ILP turns 30, we review the last decade of research. We focus on (i) new meta-level search methods, (ii) techniques for learning recursive programs, (iii) new approaches for predicate invention, and (iv) the use of different technologies. We conclude by discussing current limitations of ILP and directions for future research.
arXiv:2102.10556v2 fatcat:kv7ktjbajng6jjfae3sq3ubbmu