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From: AAAI Technical Report FS-95-04. Compilation copyright © 1995, AAAI (www.aaai.org). All rights reserved.
Adaptation
in Case-Based
Invited Talk:
Reasoning: Issues,
Methods and Directions
David Leake
Computer Science Department
Indiana University
Bloomington, IN 47405
[email protected]
http://www.cs.indiana.edu/hyplan/leake.html/
Abstract
In case-based reasoning systems, adaptation of retrieved cases plays a crucial role in flexible reuse
of stored experiences. However, despite the importance of case adaptation, the case adaptation process
remains the least understood part of case-based reasoning. The difficulty of endowingcase-based reasoning
systems with automatic case adaptation is so acute that case adaptation is often omitted from case-based
reasoning applications. In this talk I will first sketch current approaches to case adaptation, issues in
controlling the adaptation process, and howthose issues are being addressed. I will then highlight open
problems that makecase adaptation a difficult research area and suggest possible ways to alleviate them
using case-based and hybrid case-based/rule-based adaptation methods.
Brief Professional
Biography:
David Leake received his B.A. with high honors in Mathematics from Haverford College in 1980, and his
A.M. in Mathematics from Brown University in 1984. In 1990 he received his Ph.D. in Computer Science
from Yale University. He is currently an Assistant Professor of Computer Science and a memberof the
Cognitive Science faculty at Indiana University. He is the author of the book Evaluating Explanations: A
Content Theory (Lawrence Erlbaum Associates, 1992), and co-editor (with AshwinRam) of the forthcoming
volume Goal-Driven Learning. He was program chair of the AAAI-93Workshop on Case-Based Reasoning
and will present the tutorial on Case-Based Reasoning at the first International Conference on Case-Based
Reasoning, in Sesimbra, Portugal, in October of 1995.
Selected Publications:
¯ Leake, D. B. (1995). Combining rules and cases to learn case adaptation. To appear in Proceedings
of the Seventeenth Annual Conference of the Cognitive Science Society. Erlbaum.
¯ Leake, D. B. (1995). Becomingan expert case-based reasoner: Learning to adapt prior cases. Proceedings of the Eighth Annual Florida Artificial Intelligence Research Symposium.
¯ Leake, D. B. (1993). Learning adaptation strategies by introspective reasoning about memorysearch.
In D. Leake (Ed.), Case-Based Reasoning: Papers from the 1993 Workshop (Technical Report WS93-01). Menlo Park, CA: AAAIPress.
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