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Combining FOIL and EBG to Speed-Up Logic Programs (1993)
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 is shown to be an improvement over competing EBL approaches in several domains. Additionally, the algorithm is capable of automatically transforming some intractable algorithms into ones that run in polynomial time.
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Citation:
In
Proceedings of the 13th International Joint Conference on Artificial Intelligence
, pp. 1106-1111 1993. San Francisco, CA: Morgan Kaufmann.
Bibtex:
@InProceedings{zelle:ijcai93, title={Combining FOIL and EBG to Speed-Up Logic Programs}, author={John M. Zelle and Raymond J. Mooney}, booktitle={Proceedings of the 13th International Joint Conference on Artificial Intelligence}, publisher={San Francisco, CA: Morgan Kaufmann}, key={IJCAI}, pages={1106-1111}, url="http://www.cs.utexas.edu/users/ai-lab?zelle:ijcai93", year={1993} }
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