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Cartesian Genetic Programming 运行时分析布尔函数

一篇新论文分析了笛卡尔遗传编程(CGP)在演化布尔函数时的运行时。研究人员为 CGP 使用 D 个二元门构建 n 个输入的合取式建立了一个渐近界限 O(n D^5),在采用非严格选择时改进到 O(n D^4)。该研究还证明了 CGP 需要指数时间来演化异或,这一发现得到了实验结果的支持。 AI

排序理由 该集群包含一篇在 arXiv 上发表的学术论文,详细介绍了特定人工智能技术的理论分析和实验结果。

在 arXiv cs.AI 阅读 →

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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Duc-Cuong Dang, Roman Kalkreuth, Andre Opris ·

    Runtime Analysis of Cartesian Genetic Programming in Evolving Boolean Functions

    arXiv:2606.15923v1 Announce Type: cross Abstract: Cartesian Genetic Programming (CGP) is among the practical and popular forms of Genetic Programming as it uses a graph-based representation of programs. This paper presents a first runtime analysis of CGP in evolving Boolean funct…

  2. arXiv cs.NE (Neural & Evolutionary) TIER_1 English(EN) · Andre Opris ·

    Runtime Analysis of Cartesian Genetic Programming in Evolving Boolean Functions

    Cartesian Genetic Programming (CGP) is among the practical and popular forms of Genetic Programming as it uses a graph-based representation of programs. This paper presents a first runtime analysis of CGP in evolving Boolean functions using complete training sets. We prove an asy…