Preface to special issue on Inductive Logic Programming, ILP 2017 and 2018

We are pleased to present this special issue of Machine Learning Journal on Inductive Logic Programming, ILP 2017 and 2018. Inductive Logic Programming (ILP) is a field at the intersection of Machine Learning and Logic Programming, based on logic as a uniform representation language for expressing examples, background knowledge and hypotheses. Thanks to the expressiveness of first-order logic, ILP has provided an excellent means for knowledge representation and learning in relevant fields such as graph mining, multirelational data mining and statistical relational learning, not to mention other logic-based non-propositional knowledge representation frameworks. This special issue followed the 27th InternationalConference on InductiveLogic Programming, held in Orléans, France (September 4–6, 2017), and preceded the 28th edition, held in Ferrara, Italy (September 2–4, 2018). For ILP 2018, two different tracks were organized, defining six kinds of submissions: 1. a Journal Track,