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Mutagenesis as a Diversity Enhancer and Preserver in Evolution Strategies

机译:诱变作为进化策略中的多样性增强者和保存者

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摘要

Mutagenesis is a process which forces the coverage of certain zones of the search space during the generations of an evolution strategy, by keeping track of the covered ranges for the different variables in the so called gene matrix. Originally introduced as an artifact to control the automated stopping criterion in a memetic algorithm, ESLAT, it also improved the exploration capabilities of the algorithm, even though this was considered a secondary matter and not properly analyzed or tested. This work focuses on this diversity enhancement, redefining mutagenesis to increase this characteristic, measuring this improvement over a set of twenty-seven unconstrained optimization functions to provide statistically significant results.
机译:诱变是通过跟踪所谓的基因矩阵中不同变量的覆盖范围,在进化策略的生成过程中强制覆盖搜索空间某些区域的过程。最初是作为模因算法ESLAT中控制自动停止标准的工件引入的,它也提高了算法的探索能力,即使这被认为是次要问题且未进行适当的分析或测试。这项工作专注于这种多样性的增强,重新定义了诱变以增加此特性,并在一组27个无约束的优化函数中测量了这种改进,以提供具有统计意义的结果。

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  • 来源
  • 会议地点 Salamanca(ES);Salamanca(ES)
  • 作者单位

    University Carlos Ⅲ of Madrid, Computer Science Department, Group of Applied Artificial Intelligence. Avda. Universidad Carlos Ⅲ, 22, Colmenarejo, Spain;

    University Carlos Ⅲ of Madrid, Computer Science Department, Group of Applied Artificial Intelligence. Avda. Universidad Carlos Ⅲ, 22, Colmenarejo, Spain;

    University Carlos Ⅲ of Madrid, Computer Science Department, Group of Applied Artificial Intelligence. Avda. Universidad Carlos Ⅲ, 22, Colmenarejo, Spain;

    University Carlos Ⅲ of Madrid, Computer Science Department, Group of Applied Artificial Intelligence. Avda. Universidad Carlos Ⅲ, 22, Colmenarejo, Spain;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 人工智能理论;人工智能理论;
  • 关键词

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