Learning to Integrate Multiple Knowledge Sources for Case-Based Reasoning
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence. Case-based Reasoning. Pages 246-250.
Abstract
The case- based reasoning process depends on multiple overlapping knowledge sources, each of which provides an opportunity for learning. Exploiting these opportunities requires not only determining the learning mechanisms to use for each individual knowledge source, but also how the different learning mechanisms interact and their combined utility. This paper presents a case study examining the relative contributions and costs involved in learning processes for three different knowledge sources-cases, case adaptation knowledge, and similarity information-in a casebased planner. It demonstrates the importance of interactions between different learning processes and identifies a promising method for integrating multiple learning methods to improve case-based reasoning.
@inproceedings{ijcai1997p37,
title = {Learning to Integrate Multiple Knowledge Sources for Case-Based Reasoning},
author = {Leake, David B. and Kinley, Andrew and Wilson, David C.},
booktitle = {Proceedings of the Fifteenth International Joint Conference on
Artificial Intelligence, {IJCAI-97}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Martha E. Pollack},
pages = {246--250},
year = {1997},
note = {Case-based Reasoning},
url = {https://ijcai.org/proceedings/1997/37},
}
TY - CPAPER TI - Learning to Integrate Multiple Knowledge Sources for Case-Based Reasoning AU - Leake, David B. AU - Kinley, Andrew AU - Wilson, David C. T2 - Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, IJCAI-97 PB - International Joint Conferences on Artificial Intelligence PY - 1997 SP - 246 EP - 250 UR - https://ijcai.org/proceedings/1997/37 ER -Copied
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