Abstract
The accuracy-based classifier system XCS is currently the most successful learning classifier system. Several recent studies showed that XCS can produce machine-learning competitive results. Nonetheless, until now the evolutionary mechanisms in XCS remained somewhat ill-understood. This study investigates the selectorecombinative capabilities of the current XCS system. We reveal the accuracy dependence of XCS’s evolutionary algorithm and identify a fundamental limitation of the accuracy-based fitness approach in certain problems. Implications and future research directions conclude the paper.
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Tharakunnel, K.K., Butz, M.V., Goldberg, D.E. (2003). Towards Building Block Propagation in XCS: A Negative Result and Its Implications. In: Cantú-Paz, E., et al. Genetic and Evolutionary Computation — GECCO 2003. GECCO 2003. Lecture Notes in Computer Science, vol 2724. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45110-2_87
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DOI: https://doi.org/10.1007/3-540-45110-2_87
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