ILP turns 20

Authors:
Stephen Muggleton;Luc Raedt;David Poole;Ivan Bratko;Peter Flach;Katsumi Inoue;Ashwin Srinivasan
Affiliations:
Imperial College London, London, UK;Katholieke Universiteit Leuven, Leuven, Belgium;University of British Columbia, Vancouver, Canada;University of Ljubljana, Ljubljana, Slovenia;University of Bristol, Bristol, UK;National Institute of Informatics, Tokyo, Japan;South Asian University, New Delhi, India
Venue:
Machine Learning
Year:
2012

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Abstract

Inductive Logic Programming (ILP) is an area of Machine Learning which has now reached its twentieth year. Using the analogy of a human biography this paper recalls the development of the subject from its infancy through childhood and teenage years. We show how in each phase ILP has been characterised by an attempt to extend theory and implementations in tandem with the development of novel and challenging real-world applications. Lastly, by projection we suggest directions for research which will help the subject coming of age.