Advances in Inductive Logic Programming

Inductive Logic Programming is a research area situated in machine learning and logic programming, two subfields of artificial intelligence. The goal of inductive logic programming is to develop theories, techniques and tools for inducing hypotheses from observations using the representations from computational logic. Inductive Logic Programming has a high potential for applications in data mining, automated scientific discovery, knowledge discovery in databases, as well as automatic programming. This book provides a detailed state-of-the-art overview of Inductive Logic Programming as well as a collection of recent technical contributions to Inductive Logic Programming. The state-of-the-art overview is based on - among others - the successful ESPRIT basic research project no. 6020 on Inductive Logic Programming, funded by the European Commission from 1992 till 1995. It highlights some of the most important recent results within Inductive Logic Programming and can be used as a thorough introduction to the field. This book is relevant to students, researchers and practitioners of artificial intelligence and computer science, especially those concerned with machine learning, data mining and computational logic.