"Probabilistic ILP" - Tutorial

---

Intended Audience

---

Probabilistic inductive logic programming is a multi-disciplinary research area. Therefore, the tutorial is directed to a rather general audience such as machine learning, uncertainty in AI, statistical inference, inductive logic programming, multi-relational data mining etc. Basic knowledge of the three underlying constituents would be helpful, but is not necessary. The tutorial will be as self-contained as possible. The main goal of the tutorial is to provide an introduction to and a survey of approaches to probabilistic inductive logic programming. It should allow attendees to appreciate the differences and commonalities between the various statistical relational learning approaches.