A Study of the Generalization Capabilities of XCS
Pier Luca Lanzi · 1997
We analyze the generalization behavior of the XCS classifier system in environments in which only a few generalizations can be done. Experimental results presented in the paper evidence that the generalization mechanism of XCS can prevent it from learning even simple tasks in such environments. We present a new operator, named Specify, which contributes to the solution of this problem. XCS with the Specify operator, named XCSS, is compared to XCS in terms of performance and generalization capabilities in different types of environments. Experimental results show that XCSS can deal with a greater variety of environments and that it is more robust than XCS with respect to population size. 1 INTRODUCTION XCS is a classifier system recently proposed by Wilson (Wilson 1995) which has a strong tendency to evolve near-minimal populations of accurate and maximally general classifiers. Experimental results reported in the literature show that XCS can learn a more compact representation than th...