Clustering with XCS and Agglomerative Rule Merging
In this paper, the authors present a more effective approach to clustering with eXtended Classifier System (XCS) which is divided into two phases. The first phase is the XCS learning process with rule compact, during which they alter the XCS mechanisms and propose a new way to calculate rewards. After learning, the rules are evolved to form the final population consisting of rules with homogeneous data distribution. The second phase is merging the learnt rules to generate final clusters.