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 heuristics, 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 scheduling problem.
Evolutionary algorithms for reasoning in fuzzy description logics with fuzzy quantifiers / Mauro Dragoni, A.G.B. Tettamanzi - In: GECCO 2007 : genetic and evolutionary computation conference : july 7-11, 2007, University college London, Gower street, London, UK / [a cura di] Dirk Thierens ... [at al.]. - New York : ACM press, 2007. - ISBN 9781595936974. - pp. 1967-1974 (( convegno Genetic and Evolutionary Computation Conference (GECCO) tenutosi a University College, London, UK nel 2007 [10.1145/1276958.1277349].
Evolutionary algorithms for reasoning in fuzzy description logics with fuzzy quantifiers
M. Dragoni;A.G.B. TettamanziUltimo
2007
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 heuristics, 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 scheduling problem.
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