Learning Abstraction Hierarchies for Problem Solving
Abstract
The use of abstraction in problem solving is an effective approach to reducing search, but finding good abstractions is a difficult problem, even for people. This paper identifies a criterion for selecting useful abstractions, describes a tractable algorithm for generating them, and empirically demonstrates that the abstractions reduce search. The abstraction learner, called alpine, isinte- grated with the prodigy problem solver [Minton et al., 1989b, Carbonell et al.,1991] and has been tested on large problem sets in multiple domains.
Cite
Text
Knoblock. "Learning Abstraction Hierarchies for Problem Solving." AAAI Conference on Artificial Intelligence, 1990.Markdown
[Knoblock. "Learning Abstraction Hierarchies for Problem Solving." AAAI Conference on Artificial Intelligence, 1990.](https://mlanthology.org/aaai/1990/knoblock1990aaai-learning/)BibTeX
@inproceedings{knoblock1990aaai-learning,
title = {{Learning Abstraction Hierarchies for Problem Solving}},
author = {Knoblock, Craig A.},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {1990},
pages = {923-928},
url = {https://mlanthology.org/aaai/1990/knoblock1990aaai-learning/}
}