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- W4285805280 abstract "In our recent paper, What can phylogenetic metrics tell us about useful diversity in evolutionary algorithms [3], we explore the relationship between metrics of diversity based on phylogenetic topology and fitness. Our contribution is two-fold. First, we identify a technique for quantifying the relationship between diversity and fitness. Previous efforts to draw hard conclusions about this relationship had been stymied by the fact that these two properties are locked in a tight feedback loop. Second, we use this technique to assess the extent to which phylogenetic diversity leads to high-fitness solutions. We find that phylogenetic diversity is often more informative of future success in evolutionary algorithms than more commonly used diversity metrics, suggesting that is an underutilized tool in evolutionary computation research." @default.
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- W4285805280 date "2022-07-09" @default.
- W4285805280 modified "2023-09-26" @default.
- W4285805280 title "Phylogenetic diversity predicts future success in evolutionary computation" @default.
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- W4285805280 doi "https://doi.org/10.1145/3520304.3534079" @default.
- W4285805280 hasPublicationYear "2022" @default.
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