@inproceedings{ddc54be18575446e89aca3ca62d1fe02,
title = "Runtime analysis via symmetry arguments: (hot-off-the-press track at GECCO 2021)",
abstract = "We use an elementary argument building on group actions to prove that the selection-free steady state genetic algorithm analyzed by Sutton and Witt (GECCO 2019) takes an expected number of [EQUATION] iterations to find any particular target search point. This bound is valid for all population sizes µ. Our result improves and extends the previous lower bound of (exp(nd/2)) valid for population sizes = O(n1/2 - d), 0 < d < 1/2. This paper for the Hot-off-the-Press track at GECCO 2021 summarizes the work Benjamin Doerr. Runtime Analysis of Evolutionary Algorithms via Symmetry Arguments. Information Processing Letters, 166:106064. 2021. [5].",
keywords = "group actions, runtime analysis, theory",
author = "Benjamin Doerr",
note = "Publisher Copyright: {\textcopyright} 2021 Owner/Author.; 2021 Genetic and Evolutionary Computation Conference, GECCO 2021 ; Conference date: 10-07-2021 Through 14-07-2021",
year = "2021",
month = jul,
day = "7",
doi = "10.1145/3449726.3462720",
language = "English",
series = "GECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion",
publisher = "Association for Computing Machinery, Inc",
pages = "23--24",
booktitle = "GECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion",
}