ILP Turns 20 - Biography and Future Challenges

Stephen H. Muggleton, Luc De Raedt, David Poole, Ivan Bratko, Peter A. Flach, Katsumi Inoue, Ashwin Srinivasan

MLJ 2012 pp. 3-23

doi:10.1007/S10994-011-5259-2 /mlj/2012/muggleton2012mlj-ilp/

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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Text

Muggleton et al. "ILP Turns 20 - Biography and Future Challenges." Machine Learning, 2012. doi:10.1007/S10994-011-5259-2

Markdown

[Muggleton et al. "ILP Turns 20 - Biography and Future Challenges." Machine Learning, 2012.](https://mlanthology.org/mlj/2012/muggleton2012mlj-ilp/) doi:10.1007/S10994-011-5259-2

BibTeX

@article{muggleton2012mlj-ilp,
  title     = {{ILP Turns 20 - Biography and Future Challenges}},
  author    = {Muggleton, Stephen H. and De Raedt, Luc and Poole, David and Bratko, Ivan and Flach, Peter A. and Inoue, Katsumi and Srinivasan, Ashwin},
  journal   = {Machine Learning},
  year      = {2012},
  pages     = {3-23},
  doi       = {10.1007/S10994-011-5259-2},
  volume    = {86},
  url       = {https://mlanthology.org/mlj/2012/muggleton2012mlj-ilp/}
}