Sharpness-aware minimization in genetic programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Bakurov:2024:GPTP,
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author = "Illya Bakurov and Nathan Haut and Wolfgang Banzhaf",
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title = "Sharpness-aware minimization in genetic programming",
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booktitle = "Genetic Programming Theory and Practice XXI",
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year = "2024",
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editor = "Wolfgang Banzhaf and Ting Hu and
Alexander Lalejini and Stephan Winkler",
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series = "Genetic and Evolutionary Computation",
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address = "University of Michigan, USA",
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month = jun # " 6-8",
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keywords = "genetic algorithms, genetic programming, SAM",
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URL = "https://arxiv.org/abs/2405.10267",
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size = "22 pages",
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abstract = "Sharpness-Aware Minimization (SAM) was recently
introduced as a regularization procedure for training
deep neural networks. It simultaneously minimizes the
fitness (or loss) function and the so-called fitness
sharpness. The latter serves as a measure of the
nonlinear behaviour of a solution and does so by
finding solutions that lie in neighborhoods having
uniformly similar loss values across all fitness cases.
we adapt SAM for tree Genetic Programming (TGP) by
exploring the semantic neighborhoods of solutions using
two simple approaches. By capitalising upon perturbing
input and output of program trees, sharpness can be
estimated and used as a second optimization criterion
during the evolution. To better understand the impact
of this variant of SAM on TGP, we collect numerous
indicators of the evolutionary process, including
generalization ability, complexity, diversity, and a
recently proposed genotype-phenotype mapping to study
the amount of redundancy in trees. The experimental
results demonstrate that using any of the two proposed
SAM adaptations in TGP allows (i) a significant
reduction of tree sizes in the population and (ii) a
decrease in redundancy of the trees. When assessed on
real-world benchmarks, the generalization ability of
the elite solutions does not deteriorate.",
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notes = "to be published after the workshop",
- }
Genetic Programming entries for
Illya Bakurov
Nathaniel Haut
Wolfgang Banzhaf
Citations