统计离群点检测方法在自适应进化中的应用 算法

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摘要翻译：
本文重新讨论了进化算法(EA)搜索算子的自适应概率问题。设计了一个框架，以区分业绩计量和为适应目的对这些计量的解释。提供了几个测量和统计解释的例子。使用一个包含10个搜索算子的EA对10个测试问题进行了概率值自适应测试，结果表明测量类型及其统计解释对EA的性能都有重要影响。我们还发现，基于异常值的普遍程度而不是平均性能来选择算子能够为自适应方法提供相当大的改进，并显著优于非自适应方法。
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英文标题：
《Use of statistical outlier detection method in adaptive evolutionary
  algorithms》
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作者：
James M. Whitacre, Tuan Q. Pham, Ruhul A. Sarker
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最新提交年份：
2009
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Neural and Evolutionary Computing        神经与进化计算
分类描述：Covers neural networks, connectionism, genetic algorithms, artificial life, adaptive behavior. Roughly includes some material in ACM Subject Class C.1.3, I.2.6, I.5.
涵盖神经网络，连接主义，遗传算法，人工生命，自适应行为。大致包括ACM学科类C.1.3、I.2.6、I.5中的一些材料。
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一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  In this paper, the issue of adapting probabilities for Evolutionary Algorithm (EA) search operators is revisited. A framework is devised for distinguishing between measurements of performance and the interpretation of those measurements for purposes of adaptation. Several examples of measurements and statistical interpretations are provided. Probability value adaptation is tested using an EA with 10 search operators against 10 test problems with results indicating that both the type of measurement and its statistical interpretation play significant roles in EA performance. We also find that selecting operators based on the prevalence of outliers rather than on average performance is able to provide considerable improvements to adaptive methods and soundly outperforms the non-adaptive case.
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PDF链接：
https://arxiv.org/pdf/0907.0595

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关键词：Measurements Evolutionary Intelligence Presentation Improvements 搜索 interpretation 包含 概率