Analyzing parameter sensitivity and classifier representations for real-valued XCS

To evaluate a real-valued XCS classifier system, we present a validation of Wilson's XCSR from two points of view. These are: (1) sensitivity of real-valued XCS specific parameters on performance and (2) the design of classifier representation with classifier operators such as mutation and covering. We also propose model with another classifier representation (LU-Model) to compare it with a model with the original XCSR classifier representation (CS-Model.) We did comprehensive experiments by applying a 6-dimensional real-valued multiplexor problem to both models. This revealed the following: (1) there are critical threshold on covering operation parameter (r(0)), which must be considered in setting parameters to avoid serious decreases in performance; and (2) the LU-Model has an advantage in smaller classifier population size within the same performance level over the CS-Model, which reveals the superiority of alternative classifier representation for real-valued XCS.