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Speeding-up Logic Programs by Combining EBG and FOIL (1992)
John M. Zelle
and
Raymond J. Mooney
This paper presents an algorithm that combines traditional EBL techniques and recent developments in inductive logic programming to learn effective clause selection rules for Prolog programs. When these control rules are incorporated into the original program, significant speed-up may be achieved. The algorithm produces not only EBL-like speed up of problem solvers, but is capable of automatically transforming some intractable algorithms into ones that run in polynomial time.
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Citation:
In
Proceedings of the 1992 Machine Learning Workshop on Knowledge Compilation and Speedup Learning
, Aberdeen, Scotland, July 1992.
Bibtex:
@inproceedings{zelle:ml-kcsl92, title={Speeding-up Logic Programs by Combining EBG and FOIL}, author={John M. Zelle and Raymond J. Mooney}, booktitle={Proceedings of the 1992 Machine Learning Workshop on Knowledge Compilation and Speedup Learning}, month={July}, address={Aberdeen, Scotland}, url="http://www.cs.utexas.edu/users/ai-lab?zelle:ml-kcsl92", year={1992} }
People
Raymond J. Mooney
Faculty
mooney [at] cs utexas edu
John M. Zelle
Ph.D. Alumni
john zelle [at] wartburg edu
Areas of Interest
Explanation-Based Learning
Inductive Logic Programming
Learning for Planning and Problem Solving
Machine Learning
Labs
Machine Learning