Uniform-in-time mean-field limit estimate for the Consensus-Based Optimization

Fuente: arXiv
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Main Authors: Huang, Hui, Kouhkouh, Hicham
Format: Preprint
Published: 2024
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author Huang, Hui
Kouhkouh, Hicham
author_facet Huang, Hui
Kouhkouh, Hicham
contents We establish a uniform-in-time estimate for the mean-field convergence of the Consensus-Based Optimization (CBO) algorithm by rescaling the consensus point in the dynamics with a small parameter $κ\in (0,1)$. This uniform-in-time estimate is essential, as CBO convergence relies on a sufficiently large time horizon and is crucial for ensuring stable, reliable long-term convergence, the latter being key to the practical effectiveness of CBO methods.
format Preprint
id arxiv_https___arxiv_org_abs_2411_03986
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Uniform-in-time mean-field limit estimate for the Consensus-Based Optimization
Huang, Hui
Kouhkouh, Hicham
Optimization and Control
Probability
65C35, 90C26, 90C56
We establish a uniform-in-time estimate for the mean-field convergence of the Consensus-Based Optimization (CBO) algorithm by rescaling the consensus point in the dynamics with a small parameter $κ\in (0,1)$. This uniform-in-time estimate is essential, as CBO convergence relies on a sufficiently large time horizon and is crucial for ensuring stable, reliable long-term convergence, the latter being key to the practical effectiveness of CBO methods.
title Uniform-in-time mean-field limit estimate for the Consensus-Based Optimization
topic Optimization and Control
Probability
65C35, 90C26, 90C56
url https://arxiv.org/abs/2411.03986