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We present the design and implementation of an open-set textindependent speaker identification system using genetic Learning Classifier Systems (LCS). We examine the use of this system in a real-number problem domain, where there is strong interest in its application to tactical communications. We investigate different encoding methods for representing real-number knowledge and study the efficacy of each method for speaker identification. We also identify several difficulties in solving thedoi:10.1109/cisda.2007.368129 dblp:conf/cisda/WolfPOB07 fatcat:ruu6vxc46rfn7orswdroofiyca