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Abstract: One of the difficult problems in the area of explanation based learning is the utility problem; learning too many rules of low utility can lead to swamping, or degradation of performance. This paper introduces two new techniques for improving the utility of learned rules. The first technique is to combine EBL with inductive learning techniques to learn a better set of control rules; the second technique is to use these inductive techniques to learn approximate control rules. The two techniques... (Update)
Context of citations to this paper: More
.... utility problem is to use inductive learning techniques to learn simpler #or approximate# control rules with reduced match cost #Cohen, 1990; Zelle Mooney, 1993#. These approaches are on the other side of the spectrum of maintaining versus dropping #or simplifying#...
...solving examples. These approaches strongly depend on the particular examples seen, but can also acquire simple and useful rules (Cohen, 1990, Leckie and Zukerman, 1991) This article presents a method that combines a deductive and an inductive approach, integrating three...
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BibTeX entry: (Update)
W. W. Cohen. Learning approximate control rules of high utility. In ML-90, pages 268--276, Austin, TX, June 1990. http://citeseer.ist.psu.edu/article/cohen90learning.html More
@inproceedings{ cohen90learning,
author = "William W. Cohen",
title = "Learning Approximate Control Rules of High Utility",
booktitle = "Machine Learning",
pages = "268-276",
year = "1990",
url = "citeseer.ist.psu.edu/article/cohen90learning.html" }
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90 Learning effective search control knowledge: An explanation-.. (context) - Minton - 1988
54 A study of explanation-based methods for inductive learning (context) - Flann, Dietterich - 1989
29 Lazy explanationbased learning: A solution to the intractibl.. (context) - Tadepalli - 1989
24 Learning from textbook knowledge: A case study - Cohen - 1990
20 Abductive explanation based learning: A solution to the mult.. - Cohen - 1989
19 The effect of rule use on the utility of explanation based l.. (context) - Mooney - 1989
16 PROLEARN: Towards a prolog interpreter that learns (context) - Prieditis, Mostow - 1987
15 Eliminating expensive chunks by restricting expressiveness (context) - Tambe, Rosenbloom - 1989
12 Using and refining simplifications: Explanation-based learni.. (context) - Chien - 1989
9 Approximating learned search control knowledge (context) - Chase, Zweben et al. - 1989
9 The role of explicit contextual knowledge in learning concep.. (context) - Keller - 1987
6 Approximate theory formation: An explanation-based approach (context) - Ellman - 1988
5 Toward combining empirical and analytical methods for inferr.. (context) - Mitchell - 1982
3 Generalizing number in explanation based learning (context) - Shavlik - 1987
1 Utilization filtering: A method for reducing the inherit har.. (context) - Markovitch, Scott - 1989
The graph only includes citing articles where the year of publication is known.
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