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Titlebook: Learning Classifier Systems; 10th International W Jaume Bacardit,Ester Bernadó-Mansilla,Keiki Takada Conference proceedings 2008 Springer-V

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A Principled Foundation for LCS learning methods to train this model. This leads to a clear identification of the LCS model and makes explicit the assumptions made about the data, as well as promises advances in the theoretical understanding of LCS through transferring the understanding of the applied machine learning methods to
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Revisiting UCS: Description, Fitness Sharing, and Comparison with XCSsed learning scheme. A complete description of the system is given with the aim of being useful as an implementation guide. Besides, we review the fitness computation, based on the individual accuracy of each rule, and introduce a fitness sharing scheme to UCS. We analyze the dynamics of UCS both wi
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