• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Machine learning >Representing and Learning Quality-Improving Search Control Knowledge
【24h】

Representing and Learning Quality-Improving Search Control Knowledge

机译：表示和学习质量-改善搜索控制知识

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Generating good, production-quality plans is an essential element in transforming planners from research tools into real-world applications, but one that has been frequently overlooked in research on machine learning for planning. This paper describes quality, an architecture that automatically acquires operational quality-improving control knowledge given a domain theory, a domain-specific metric of plan quality, and problems which provide planning experience. The framework includes two distinct domain-independent learning mechanisms which differ in the language used to represent the learned knowledge, namely control rules and control knowledge trees, and in the kinds of quality metrics for which they are best suited. QUALITY is fully implemented on top of the PRODIGY4.0 nonlinear planner and its empirical evaluation has shown that the learned knowledge is able to substantially improve plan quality. Although the learning mechanisms have been developed for prodigy4.0, the framework is general and addresses a problem confronted by any planner that treats planning as a constructive decision-making process.
机译：生成优质的生产质量计划是将计划者从研究工具转变为现实应用程序的基本要素，但是在机器学习计划研究中却经常被忽略。本文描述了质量，给定领域理论的，自动获取可提高操作质量的控制知识的体系结构，计划质量的领域特定度量以及提供计划经验的问题。该框架包括两个不同的领域无关的学习机制，它们在表示学习到的知识所用的语言（即控制规则和控制知识树）以及最适合它们的质量度量类型方面有所不同。质量是在PRODIGY4.0非线性计划程序的基础上完全实现的，其经验评估表明，所学的知识能够显着提高计划质量。尽管已经为prodigy4.0开发了学习机制，但是该框架是通用的，可以解决任何将计划视为建设性决策过程的计划者所面临的问题。

著录项

  • 来源
    《Machine learning》|1996年|382-390|共9页
  • 会议地点 Bari(IT);Bari(IT)
  • 作者

    M. Alicia Perez;

  • 作者单位

    Computer Science Department Boston College Chestnut Hill, MA 02167;

  • 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

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号