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Evolutionary algorithms for reasoning in fuzzy description logics with fuzzy quantifiers
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Genetic And Evolutionary Computation Conference archive
Proceedings of the 9th annual conference on Genetic and evolutionary computation table of contents
London, England
SESSION: Real-world applications: papers table of contents
Pages: 1967 - 1974  
Year of Publication: 2007
ISBN:978-1-59593-697-4
Authors
Mauro Dragoni  Università degli Studi
Andrea G. B. Tettamanzi  Università degli Studi
Sponsors
SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Mauro Dragoni: colleagues
Andrea G. B. Tettamanzi: colleagues