NEXTPITCH, a learning classifier system (LCS) using genetic algorithms, inductively learns to predict the next note in a musical melody. NEXTPITCH models human music learning by developing the rules that represent actual pitch transitions in the melody. In this article, the author addresses the issues of (1) the impact of the representation of a domain (the encoding of the characteristics of the field of study) on the performance of an LCS and (2) the classification of the input (the melodies to be learned) to an LCS in order to determine the highest percentage of correct next-note predictions.

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