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The Generate, Test, and Explain Discovery System Architecture

机译:生成,测试和解释发现系统架构

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摘要

Discovery systems have the potential to make truly novel discoveries, although few of them actually do so. Because original discoveries are difficult to understand even when they are explained in lucid prose, discovery systems that make new discoveries should provide explanations of them that are easy for humans to understand, lest they go unnoticed. The generate, test, and explain discovery system architecture moves the machine discovery field a step closer to these two goals by: (1) Demonstrating on two real-world problems, financial time series analysis and secondary structure prediction, that discovery systems can deliver on their promise to make novel discoveries; and (2) Extending the autonomy of discovery systems with an explanation facility that rephrases discoveries in terms that are easy to understand.
机译:发现系统有可能做出真正新颖的发现,尽管实际上很少有人这样做。因为即使在清晰的散文中对原始发现进行​​解释也很难理解,所以进行新发现的发现系统应提供易于人类理解的解释,以免被忽视。生成,测试和解释发现系统体系结构通过以下方式使机器发现领域更接近这两个目标:(1)演示发现系统可以实现的两个实际问题,即财务时间序列分析和二级结构预测他们做出新发现的承诺; (2)通过解释工具扩展发现系统的自治性,该解释工具以易于理解的术语重新描述发现。

著录项

  • 来源
    《Machine learning》|1994年|46-52|共7页
  • 会议地点 New Brunswick NJ(US);New Brunswick NJ(US)
  • 作者

    Michael de la Maza;

  • 作者单位

    Numinous Noetics Group Artificial Intelligence Laboratory Massachusetts Institute of Technology Room NE43-815 545 Technology Square Cambridge, MA 02139;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 计算机的应用;
  • 关键词

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