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ILP turns 20

by: Stephen Muggleton, Luc Raedt, David Poole, Ivan Bratko, Peter Flach, Katsumi Inoue, Ashwin Srinivasan
Machine Learning In Machine Learning, Vol. 86, No. 1. (5 September 2012), pp. 3-23, doi:10.1007/s10994-011-5259-2  Key: citeulike:9813534

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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.


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