An Algorithm for Adaptation in Case-based Reasoning
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Auteurs : Béatrice Fuchs ; Jean Lieber ; Alain Mille ; Amedeo NapoliSource :
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Abstract
The adaptation process is an important and complex step of case-based reasoning (CBR) and is most of the time designed for a specific application. This article presents a domain-independent algorithm for adaptation in CBR. Cases are mapped to a set of numerical descriptors filled with values and local constraint intervals. The algorithm computes every target solution descriptor by combining a source solution, a matching expressed as intervals of variations and dependencies between the source problem and its solution. It determines for every target solution descriptor an interval of the admissible values. In this interval, actual values satisfying global constraints can be chosen. This generic approach to adaptation is operational and introduces general and domain-independent adaptation operators. Therefore, this study is a contribution to the design of a general algorithm for adaptation in CBR.
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<author><name sortKey="Lieber, Jean" sort="Lieber, Jean" uniqKey="Lieber J" first="Jean" last="Lieber">Jean Lieber</name>
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<author><name sortKey="Mille, Alain" sort="Mille, Alain" uniqKey="Mille A" first="Alain" last="Mille">Alain Mille</name>
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<author><name sortKey="Napoli, Amedeo" sort="Napoli, Amedeo" uniqKey="Napoli A" first="Amedeo" last="Napoli">Amedeo Napoli</name>
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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>adaptation</term>
<term>case-based reasoning</term>
<term>domain-independant adaptation</term>
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<front><div type="abstract" xml:lang="en" wicri:score="3057">The adaptation process is an important and complex step of case-based reasoning (CBR) and is most of the time designed for a specific application. This article presents a domain-independent algorithm for adaptation in CBR. Cases are mapped to a set of numerical descriptors filled with values and local constraint intervals. The algorithm computes every target solution descriptor by combining a source solution, a matching expressed as intervals of variations and dependencies between the source problem and its solution. It determines for every target solution descriptor an interval of the admissible values. In this interval, actual values satisfying global constraints can be chosen. This generic approach to adaptation is operational and introduces general and domain-independent adaptation operators. Therefore, this study is a contribution to the design of a general algorithm for adaptation in CBR.</div>
</front>
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<BibTex type="inproceedings"><ref>fuchs00a</ref>
<crinnumber>A00-R-163</crinnumber>
<category>3</category>
<equipe>IAE-Modeme</equipe>
<author><e>Fuchs, Béatrice</e>
<e>Lieber, Jean</e>
<e>Mille, Alain</e>
<e>Napoli, Amedeo</e>
</author>
<title>An Algorithm for Adaptation in Case-based Reasoning</title>
<booktitle>{14th European Conference on Artificial Intelligence - ECAI'2000, Berlin, Germany}</booktitle>
<year>2000</year>
<editor>Werner Horn</editor>
<pages>45-49</pages>
<address>Amsterdam</address>
<month>Aug</month>
<publisher>IOS Press</publisher>
<url>http://www.loria.fr/publications/2000/A00-R-163/A00-R-163.ps</url>
<keywords><e>case-based reasoning</e>
<e>adaptation</e>
<e>domain-independant adaptation</e>
</keywords>
<abstract>The adaptation process is an important and complex step of case-based reasoning (CBR) and is most of the time designed for a specific application. This article presents a domain-independent algorithm for adaptation in CBR. Cases are mapped to a set of numerical descriptors filled with values and local constraint intervals. The algorithm computes every target solution descriptor by combining a source solution, a matching expressed as intervals of variations and dependencies between the source problem and its solution. It determines for every target solution descriptor an interval of the admissible values. In this interval, actual values satisfying global constraints can be chosen. This generic approach to adaptation is operational and introduces general and domain-independent adaptation operators. Therefore, this study is a contribution to the design of a general algorithm for adaptation in CBR.</abstract>
</BibTex>
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