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Lecture Notes in Computer Science
XCS has been shown to solve hard problems in a machine-learning competitive way. Recent theoretical advancements show that the system can scale-up polynomially in the problem complexity and problem size given the problem is a k-DNF with certain properties. This paper addresses two major issues in XCS: (1) knowledge extraction and (2) structure identification. Knowledge extraction addresses the issue of mining problem knowledge from the final solution developed by XCS. The goal is to identifydoi:10.1007/978-3-540-30217-9_106 fatcat:pp277lt5dfgu5dtcaipvbkvhzu