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"Genetic Inductive Logic Programming"

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Authors: Amund Tveit

Abstract:
The most used method of finding logical rules from data, inductive logic programming (ILP), has shown successful, but unfortunately not very scalable with increasing problem size. In this report a model for doing induction of logical rules, using the concepts of the potentially more scalable method of genetic algorithm, is suggested.

Five strategies of reducing the search space in the representation are suggested: pruning by logical entailment, pruning by integrity constraints, pruning by logic factorization, pruning by range restrictedness, and pruning using a heuristic fitness function on the cohesion of literals. The genetic operators suggested are applying these pruning search strategies.

The model has yet to be implemented and tried out in an experimental setting.

Keywords: Inductive Logic Programming, Genetic Algorithms, Optimalization, Logic

Bibtex Citation

@MastersThesis{GILP1997Tveit,
  author  = 	 {Amund Tveit},
  title   = 	 {Genetic Inductive Logic Programming},
  school  = 	 {Department of Computer and Information Science, Norwegian University of Science and Technology},
  year    = 	 {1997},
  address = 	 {IDI/NTNU, N-7491 Trondheim, Norway},
  month   = 	 {December}
}

Cited by:

  1. "Growth Phenomen of Individual's Code Length in Genetic Inductive Logic Programming", Journal of Computer Research and Development, volume 40, number 8, pp 1238--1243, Wanfang Data, 2003

  2. David Gleich. "Machine Learning in Computer Chess: Genetic Programming and KRK", Technical Report, Harvey Mudd College, 2003

  3. Tim Fuhner and Gabriella Kokai. "Incorporating Linkage Learning into the GeLog Framework", In Acta Cybernetica, Volume 16, Number 2, 2003, published by Institute of Informatics, University of Szeged, Hungary, 2003

  4. "Using Genetic Algorithm to Mine First-order Rules", Journal of Computer Engineering and Applications (Wanfang data/Chinainfo), Volume 38, Number 17, pp 28--30, China, 2002

  5. Gabriella Kokai. "Erfolge und Probleme evolutionarer Algorithmen, inductive logischer Programmeriung und ihrer Kombination", Dr.ing thesis, University of Nurnberg, Germany

  6. Gabriella Kokai. "GeLog - A System Combining Genetic Algorithm with Inductive Logic Programming", In Proceedings of the International Conference on Computational Intelligence, Lecture Notes in Computer Science (LNCS) 2206, Springer-Verlag, October 1-3, 2001, 326--345
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