Remembering to Add: Competence-Preserving Case-Addition Policies for Case Base Maintenance
Abstract
Case-base maintenance is gaining increasing recognition in research and the practical applications of case-based reasoning (CBR). This intense interest is highlighted by Smyth and Keane's research on case deletion policies. In their work, Smyth and Keane advocated a case deletion policy, whereby the cases in a case base are classified and deleted based on their coverage potential and adaptation power. The algorithm was empirically shown to improve the competence of a CBR system and outperform a number of previous deletion-based strategies. In this paper, we present a different case-base maintenance policy that is based on case addition rather than deletion. The advantage of our algorithm is that we can place a lower bound on the competence of the resulting case base; we demonstrate that the coverage of the computed case base cannot be worse than the optimal case base in coverage by a fixed lower bound, and the coverage is often much closer to optimum. We also show that the Smyth and Ke...
Cite
Text
Zhu and Yang. "Remembering to Add: Competence-Preserving Case-Addition Policies for Case Base Maintenance." International Joint Conference on Artificial Intelligence, 1999.Markdown
[Zhu and Yang. "Remembering to Add: Competence-Preserving Case-Addition Policies for Case Base Maintenance." International Joint Conference on Artificial Intelligence, 1999.](https://mlanthology.org/ijcai/1999/zhu1999ijcai-remembering/)BibTeX
@inproceedings{zhu1999ijcai-remembering,
title = {{Remembering to Add: Competence-Preserving Case-Addition Policies for Case Base Maintenance}},
author = {Zhu, Jun and Yang, Qiang},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {1999},
pages = {234-241},
url = {https://mlanthology.org/ijcai/1999/zhu1999ijcai-remembering/}
}