Atsushi WADA, Keiki TAKADAMA, Katsunori SHIMOHARA, Osamu KATAI
Analyzing Parameter Sensitivity and
Classifier Representations for
Real-valued XCS
Abstract: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 (ro), 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.