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After almost forty years of development, fuzzy systems have demonstrated their superb ability to solve different problems arising in various application domains. In the last two decades, the cooperative framework established made the research interest move to augment fuzzy systems with learning and adaptation capabilities. Since the first pioneer works dated back to 1991, one of the most successful approaches to hybridize fuzzy systems with learning and adaptation methods, apart of course from fuzzy neural networks, has resulted in so-called Genetic Fuzzy Systems. These hybrid computational intelligence techniques augment the approximate reasoning method of fuzzy systems with the learning capabilities of evolutionary algorithms.
The aim of the session is to provide a forum to disseminate and discuss recent and significant research efforts on Genetic Fuzzy Systems in order to deal with current challenges on this topic. The session is therefore open to any high quality submission from researchers working at the particular intersection of evolutionary algorithms and fuzzy systems called Genetic Fuzzy Systems. Potential authors for this Special Session should present original research and innovative results including (but not limited to) the following topics:
All submissions will be refereed by at least three experts in the field based on originality, significance, quality and clarity. Every submitted paper to HAIS'08 will be reviewed by at least two members of the Program Committee. Accepted contributions are to be published in the HAIS'08 Proceedings.
NOTICE: At least one author of each accepted paper must register in order for the paper to be included in the HAIS 2008 Proceedings.
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Evolutionary Learning/Tuning of Fuzzy Rule-Based Systems
Papers must be prepared according to the LNCS-LNAI styletemplate (only
MS-WORD format) (see: 
Deadline for papers: 30th April, 2008
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