Acquiring case adaptation knowledge: A hybrid approach
Abstract
The ability of case-based reasoning (CBR) systems to apply cases to novel situations depends on their case adaptation knowledge. However, endowing CBR systems with adequate adaptation knowledge has proven to be a very difficult task. This paper describes a hybrid method for performing case adaptation, using a combination of rule-based and case-based reasoning. It shows how this approach provides a framework for acquiring flexible adaptation knowledge from experiences with autonomous adaptation and suggests its potential as a basis for acquisition of adaptation knowledge from interactive user guidance. It also presents initial experimental results examining the benefits of the approach and comparing the relative contributions of case learning and adaptation learning to reasoning performance.
- Authors:
-
- Indiana Univ., Bloomington, IN (United States)
- Publication Date:
- OSTI Identifier:
- 430728
- Report Number(s):
- CONF-960876-
TRN: 96:006521-0103
- Resource Type:
- Conference
- Resource Relation:
- Conference: 13. National conference on artifical intelligence and the 8. Innovative applications of artificial intelligence conference, Portland, OR (United States), 4-8 Aug 1996; Other Information: PBD: 1996; Related Information: Is Part Of Proceedings of the thirteenth national conference on artificial intelligence and the eighth innovative applications of artificial intelligence conference. Volume 1 and 2; PB: 1626 p.
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 99 MATHEMATICS, COMPUTERS, INFORMATION SCIENCE, MANAGEMENT, LAW, MISCELLANEOUS; ARTIFICIAL INTELLIGENCE; LEARNING; DECISION MAKING
Citation Formats
Leake, D B, Kinley, A, and Wilson, D. Acquiring case adaptation knowledge: A hybrid approach. United States: N. p., 1996.
Web.
Leake, D B, Kinley, A, & Wilson, D. Acquiring case adaptation knowledge: A hybrid approach. United States.
Leake, D B, Kinley, A, and Wilson, D. 1996.
"Acquiring case adaptation knowledge: A hybrid approach". United States.
@article{osti_430728,
title = {Acquiring case adaptation knowledge: A hybrid approach},
author = {Leake, D B and Kinley, A and Wilson, D},
abstractNote = {The ability of case-based reasoning (CBR) systems to apply cases to novel situations depends on their case adaptation knowledge. However, endowing CBR systems with adequate adaptation knowledge has proven to be a very difficult task. This paper describes a hybrid method for performing case adaptation, using a combination of rule-based and case-based reasoning. It shows how this approach provides a framework for acquiring flexible adaptation knowledge from experiences with autonomous adaptation and suggests its potential as a basis for acquisition of adaptation knowledge from interactive user guidance. It also presents initial experimental results examining the benefits of the approach and comparing the relative contributions of case learning and adaptation learning to reasoning performance.},
doi = {},
url = {https://www.osti.gov/biblio/430728},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Dec 31 00:00:00 EST 1996},
month = {Tue Dec 31 00:00:00 EST 1996}
}