Due to the accuracy based fitness approach, the ultimate goal for XCS is the evolution of a compact, complete, and accurate payoff mapping of an environment. This paper investigates what causes the XCS classifier system to evolve accurate classifiers. The investigation leads to two challenges for XCS, the covering challenge and the schema challenge. Both challenges are revealed theoretically and experimentally. Furthermore, the paper provides suggestions for overcoming the challenges as well as investigates environmental properties that can help XCS to overcome the challenges autonomously. Along those lines, a deeper insight into how to set the initial parameter values in XCS is provided.
|Translated title of the contribution||How XCS Evolves Accurate Classifiers|
|Title of host publication||Unknown|
|Editors||Lee Spector et al.|
|Pages||927 - 934|
|Number of pages||7|
|Publication status||Published - Jul 2001|