UMDA with Random Affine Maps

doi:10.1007/978-3-032-07998-5_16

2026-01-01

PRE

Arnaud Berny

DOI：10.1007/978-3-032-07998-5_16

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我们提出通过在位向量上应用随机仿射映射来扩展UMDA的概率模型。为限制复杂性，仿射映射的位矩阵表示为简单且可逆的位操作序列，称为转射。我们考虑了两种带有随机仿射映射（RAMU）的UMDA版本，分别更新一个或两个概率向量。我们提供了固定预算实验来探究RAMU的行为，并将其与UMDA进行比较。

Keyword:

Estimation of distribution algorithms

UMDA

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ARTIFICIAL EVOLUTION, EA 2024

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