ML Anthology

Refining a Relational Theory with Multiple Faults in the Concept and Subconcepts

Somkiat Tangkitvanich, Masamichi Shimura
ICML 1992 pp. 436-444
doi:10.1016/B978-1-55860-247-2.50061-9 /icml/1992/tangkitvanich1992icml-refining/

Abstract

We present a system that automatically refines the theory expressed in the function-free first-order logic. Our system can efficiently correct multiple faults in the concept and subconcepts of a theory, given only the classified examples of the concept. It can refine larger classes of theory than existing systems can since it has overcome many of their limitations. Our system is based on a new combination of an inductive and an explanation-based learning algorithms. From a learning perspective, our system is an improvement over the FOIL learning system in that our system can accept a theory as well as examples. The system has been successfully tested in refining a chemical theory.

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Cite

Text

Tangkitvanich and Shimura. "Refining a Relational Theory with Multiple Faults in the Concept and Subconcepts." International Conference on Machine Learning, 1992. doi:10.1016/B978-1-55860-247-2.50061-9

Markdown

[Tangkitvanich and Shimura. "Refining a Relational Theory with Multiple Faults in the Concept and Subconcepts." International Conference on Machine Learning, 1992.](https://mlanthology.org/icml/1992/tangkitvanich1992icml-refining/) doi:10.1016/B978-1-55860-247-2.50061-9

BibTeX

@inproceedings{tangkitvanich1992icml-refining,
  title     = {{Refining a Relational Theory with Multiple Faults in the Concept and Subconcepts}},
  author    = {Tangkitvanich, Somkiat and Shimura, Masamichi},
  booktitle = {International Conference on Machine Learning},
  year      = {1992},
  pages     = {436-444},
  doi       = {10.1016/B978-1-55860-247-2.50061-9},
  url       = {https://mlanthology.org/icml/1992/tangkitvanich1992icml-refining/}
}