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Evolutionary algorithms for reasoning in fuzzy description logics with fuzzy quantifiers

Published: 07 July 2007 Publication History

Abstract

The task of reasoning with fuzzy description logics with fuzzy quantification is approached by means of an evolutionary algorithm. An essential ingredient of the proposed method is a heuristic, implemented as an intelligent mutation operator, which observes the evolutionary process and uses the information gathered to guess at the mutations most likely to bring about an improvement of the solutions. The viability of the method is demonstrated by applying it to reasoning on a resource sheduling problem.

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Cited By

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  • (2018)Reasoning with fuzzy extensions of OWL and OWL 2Knowledge and Information Systems10.1007/s10115-013-0641-y40:1(205-242)Online publication date: 30-Dec-2018
  • (2018)Learning Fuzzy User Models for News Recommender SystemsAI*IA 2018 – Advances in Artificial Intelligence10.1007/978-3-030-03840-3_37(502-515)Online publication date: 9-Nov-2018

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cover image ACM Conferences
GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation
July 2007
2313 pages
ISBN:9781595936974
DOI:10.1145/1276958
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Published: 07 July 2007

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Author Tags

  1. description logics
  2. evolutionary algorithms
  3. fuzzy logic
  4. fuzzy quantification

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GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;
Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

View all
  • (2018)Reasoning with fuzzy extensions of OWL and OWL 2Knowledge and Information Systems10.1007/s10115-013-0641-y40:1(205-242)Online publication date: 30-Dec-2018
  • (2018)Learning Fuzzy User Models for News Recommender SystemsAI*IA 2018 – Advances in Artificial Intelligence10.1007/978-3-030-03840-3_37(502-515)Online publication date: 9-Nov-2018

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