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Computer Science > Neural and Evolutionary Computing

arXiv:2304.01978 (cs)
[Submitted on 4 Apr 2023 (v1), last revised 17 Apr 2023 (this version, v2)]

Title:A Static Analysis of Informed Down-Samples

Authors:Ryan Boldi, Alexander Lalejini, Thomas Helmuth, Lee Spector
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Abstract:We present an analysis of the loss of population-level test coverage induced by different down-sampling strategies when combined with lexicase selection. We study recorded populations from the first generation of genetic programming runs, as well as entirely synthetic populations. Our findings verify the hypothesis that informed down-sampling better maintains population-level test coverage when compared to random down-sampling. Additionally, we show that both forms of down-sampling cause greater test coverage loss than standard lexicase selection with no down-sampling. However, given more information about the population, we found that informed down-sampling can further reduce its test coverage loss. We also recommend wider adoption of the static population analyses we present in this work.
Comments: Accepted to the Genetic and Evolutionary Computation Conference 2023
Subjects: Neural and Evolutionary Computing (cs.NE)
Cite as: arXiv:2304.01978 [cs.NE]
  (or arXiv:2304.01978v2 [cs.NE] for this version)
  https://doi.org/10.48550/arXiv.2304.01978
Related DOI: https://doi.org/10.1145/3583133.3590751

Submission history

From: Ryan Boldi [view email]
[v1] Tue, 4 Apr 2023 17:34:48 UTC (1,124 KB)
[v2] Mon, 17 Apr 2023 00:00:36 UTC (1,289 KB)
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