2021/02/21 by Andrew Cropper, Cropper, Andrew, Sebastijan Dumančić +6 · 1 voice · 8 citations
Computer Science · #Advanced Algebra and Logic #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Logic, Reasoning, and Knowledge #Machine Learning (cs.LG) #Software Engineering Research #cs.AI #cs.LG
paper · pdf · doi:10.48550/arxiv.2102.10556
openalex publication_date 2021/02/21 · arxiv published 2021/02/21 · arxiv updated 2021/09/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.