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Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

Abstract

Lexicase selection is one of the most successful parent selection methods in evolutionary computation. However, it has the drawback of being a more computationally involved process and thus taking more time compared to other selection methods, such as tournament selection. Here, we study a version of lexicase selection where test cases are combined into several composite errors, called summed batch lexicase selection; the hope being faster but still reasonable success. Runs on some software synthesis problems show that a larger batch size tends to reduce the success rate of runs, but the results are not very conclusive as the number of software synthesis problems tested was small.

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