Identifying Knowledge Base Deficiencies by Observing User Behavior
Abstract
We are developing an application of explanation based learning to refine and complete the knowledge base of an expert pilot's assistant. A companion paper in this volume reports on the issues specific to planning and temporal (Perschbacher, Levi & Shalin.) In this paper we focus on the role of learning experiences in our project, and how they are used to direct the refinement of the knowledge base of the pilot's assistant. The knowledge base of the assistant must share a representation of actions and goals that is common to the user in order to coordinate activity with the user. The first knowledge base refinement problem in this project is to identify deficiencies in the system's knowledge base by observing and explaining unexpected user behavior. The second knowledge base refinement problem is to refine the knowledge base of the underlying EBL system. We present our approach to the first problem, and some comments on the second problem.
Cite
Text
Levi et al. "Identifying Knowledge Base Deficiencies by Observing User Behavior." International Conference on Machine Learning, 1989. doi:10.1016/B978-1-55860-036-2.50080-1Markdown
[Levi et al. "Identifying Knowledge Base Deficiencies by Observing User Behavior." International Conference on Machine Learning, 1989.](https://mlanthology.org/icml/1989/levi1989icml-identifying/) doi:10.1016/B978-1-55860-036-2.50080-1BibTeX
@inproceedings{levi1989icml-identifying,
title = {{Identifying Knowledge Base Deficiencies by Observing User Behavior}},
author = {Levi, Keith R. and Shalin, Valerie L. and Perschbacher, David L.},
booktitle = {International Conference on Machine Learning},
year = {1989},
pages = {296-301},
doi = {10.1016/B978-1-55860-036-2.50080-1},
url = {https://mlanthology.org/icml/1989/levi1989icml-identifying/}
}