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"Mutation Amplification and Encoding Fragility in Bit-Masked Evolutionary Landscapes"

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DataCite Commons2026-03-09 更新2026-05-03 收录
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https://ieee-dataport.org/documents/mutation-amplification-and-encoding-fragility-bit-masked-evolutionary-landscapes
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资源简介:
"This dataset contains raw and aggregated simulation results used to generate all figures in the manuscript. The experiments compare binary and Gray encodings under matched normalized mutation pressure across multiple genome sizes and environments. Each configuration was evaluated across 30 independent seeds. The dataset includes raw seed-level outputs, aggregated summaries used for plotting, and experiment configuration files.Results support two principal findings:1. Gray encoding produces consistently higher long-run population error than binary encoding across all tested mutation intensities, including under single-bit mutation.2. Performance curves across genome sizes exhibit approximate collapse when plotted against normalized mutation pressure \u03c1 = I \/ M(n), where M(n) = 8n + 64."
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IEEE DataPort
创建时间:
2026-03-09
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