Abstract

We present FIXCS (fuzzy implementation of XCS), a learning classifier system that extend the accuracy-based extended classifier system (XCS) by allowing to match real-valued input by fuzzy sets, and to produce a fuzzy output, then translated into real values. This work gives XCS the ability to face real-valued problems with a fuzzy model that approximates a real valued function better than the original, interval-based model. First results show that, as expected, the learning time is longer, but the obtained fuzzy system is more robust than the interval-based one.

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