Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A probabilistic definition of a nonconvex fuzzy cardinality
Fuzzy Sets and Systems
The description logic handbook: theory, implementation, and applications
The description logic handbook: theory, implementation, and applications
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Evolutionary Computation
GASAT: a genetic local search algorithm for the satisfiability problem
Evolutionary Computation
Reasoning within fuzzy description logics
Journal of Artificial Intelligence Research
Some complexity results on fuzzy description logics
WILF'03 Proceedings of the 5th international conference on Fuzzy Logic and Applications
Genetic-fuzzy approach to the Boolean satisfiability problem
IEEE Transactions on Evolutionary Computation
Learning Fuzzy Models of User Interests in a Semantic Information Retrieval System
Proceedings of the 2010 conference on STAIRS 2010: Proceedings of the Fifth Starting AI Researchers' Symposium
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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.