Search for: [Abstract = "Learning Classifier Systems \(LCSs\) have gained increasing interest in the genetic and evolutionary computation literature. Many real\-world problems are not conveniently expressed using the ternary representation typically used by LCSs and for such problems an interval\-based representation is preferable. A new model of LCSs is introduced to classify realvalued data. The approach applies the continous\-valued context\-free grammar\-based system GCS. In order to handle data effectively, the terminal rules were replaced by the so\-called environment probing rules. The rGCS model was tested on the checkerboard problem."]

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