The voting algorithm is robust to various noise models

DOI10.1016/j.tcs.2023.113844OpenAlexW4361284816MaRDI QIDQ2700787

Jonathan E. Rowe Aishwaryaprajna

Publication date: 27 April 2023

Published in: Theoretical Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.tcs.2023.113844

zbMATH Keywords

noisevotingrecombination

Mathematics Subject Classification ID

Theory of computing (68Qxx)

Cites Work

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• Efficient Optimisation of Noisy Fitness Functions with Population-based Evolutionary Algorithms
• Run-Time Analysis of Population-Based Evolutionary Algorithm in Noisy Environments
• The benefits and limitations of voting mechanisms in evolutionary optimisation
• Black-box search by elimination of fitness functions
• Chebyshev-Gr\"{u}ss-type inequalities via discrete oscillations
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