Comparison of strategies based on evolutionary computation for the design of similarity functions

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3 Citations (Scopus)

Abstract

One of the main keys in case-based reasoning system is the retrieval phase, where the most similar cases are retrieved by means of a similarity function. According to the problem, the similarity function must be selected and adapted depending on the characteristics and properties of the problem's domain. The goal of this article is to present a platform called BRAIN, which incorporates strategies based on different evolutionary approaches to design similarity functions ad hoc for a domain to be used in a case-based reasoning system. The strategies are based on Genetic Programming and Grammar Evolution approaches. Both are applied to different data sets to study the influence of their characteristic in the accuracy rate and in the execution time.

Original languageEnglish
Title of host publicationArtificial Intelligence Research and Development
Pages231-238
Number of pages8
Publication statusPublished - 2005
Event8th Catalan Conference on Artificial Intelligence, CCIA 2005 - Alguer, Italy
Duration: 26 Oct 200528 Oct 2005

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume131
ISSN (Print)0922-6389

Conference

Conference8th Catalan Conference on Artificial Intelligence, CCIA 2005
Country/TerritoryItaly
CityAlguer
Period26/10/0528/10/05

Keywords

  • Case Base Reasoning
  • Genetic Programmming
  • Grammar Evolution
  • Machine Learning
  • Reasoning Models
  • Similarity Function

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