D. ?Leake, A. Kinley, and D. Wilson. Proceedings of the Eighteenth Annual Conference of the Cognitive Science Society, (1996)
Abstract
The case-based reasoning (CBR) process solves problems by
retrieving prior solutions and adapting them to fit new
circumstances. Many studies examine how case-based reasoners
learn by storing new cases and refining the indices used to
retrieve cases. However, little attention has been given to
learning to refine the process for applying retrieved cases. This
paper describes research investigating how a case-based reasoner
can learn strategies for adapting prior cases to fit new
situations, and how its similarity criteria may be refined
pragmatically to reflect new capabilities for case adaptation. We
begin by highlighting psychological research on the development
of similarity criteria and summarizing our model of case
adaptation learning. We then discuss initial steps towards
pragmatically refining similarity criteria based on experiences
with case adaptation.
%0 Conference Paper
%1 LeakeKinleyWilson96a
%A ?Leake, David B.
%A Kinley, Andrew
%A Wilson, David
%B Proceedings of the Eighteenth Annual Conference of the Cognitive Science Society
%D 1996
%K imported
%T Linking Adaptation and Similarity Learning
%X The case-based reasoning (CBR) process solves problems by
retrieving prior solutions and adapting them to fit new
circumstances. Many studies examine how case-based reasoners
learn by storing new cases and refining the indices used to
retrieve cases. However, little attention has been given to
learning to refine the process for applying retrieved cases. This
paper describes research investigating how a case-based reasoner
can learn strategies for adapting prior cases to fit new
situations, and how its similarity criteria may be refined
pragmatically to reflect new capabilities for case adaptation. We
begin by highlighting psychological research on the development
of similarity criteria and summarizing our model of case
adaptation learning. We then discuss initial steps towards
pragmatically refining similarity criteria based on experiences
with case adaptation.
@inproceedings{LeakeKinleyWilson96a,
abstract = {The case-based reasoning (CBR) process solves problems by
retrieving prior solutions and adapting them to fit new
circumstances. Many studies examine how case-based reasoners
learn by storing new cases and refining the indices used to
retrieve cases. However, little attention has been given to
learning to refine the process for applying retrieved cases. This
paper describes research investigating how a case-based reasoner
can learn strategies for adapting prior cases to fit new
situations, and how its similarity criteria may be refined
pragmatically to reflect new capabilities for case adaptation. We
begin by highlighting psychological research on the development
of similarity criteria and summarizing our model of case
adaptation learning. We then discuss initial steps towards
pragmatically refining similarity criteria based on experiences
with case adaptation.},
added-at = {2006-11-14T09:19:23.000+0100},
author = {?Leake, David B. and Kinley, Andrew and Wilson, David},
biburl = {https://www.bibsonomy.org/bibtex/2879fd3327e52479d027148f3d97a829c/thorob67},
booktitle = {Proceedings of the Eighteenth Annual Conference of the Cognitive Science Society},
interhash = {467fc9db3a293dc0281b3123f34a2875},
intrahash = {879fd3327e52479d027148f3d97a829c},
keywords = {imported},
timestamp = {2006-11-14T09:19:23.000+0100},
title = {Linking Adaptation and Similarity Learning},
year = 1996
}