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Cogitator : a parallel, fuzzy, database-driven expert system

机译:搅拌器:并行,模糊,数据库驱动的专家系统

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摘要

The quest to build anthropomorphic machines has led researchers to focus on knowledge and the manipulation thereof. Recently, the expert system was proposed as a solution, working well in small, well understood domains. However these initial attempts highlighted the tedious process associated with building systems to display intelligence, the most notable being the Knowledge Acquisition Bottleneck. Attempts to circumvent this problem have led researchers to propose the use of machine learning databases as a source of knowledge. Attempts to utilise databases as sources of knowledge has led to the development Database-Driven Expert Systems. Furthermore, it has been ascertained that a requisite for intelligent systems is powerful computation. In response to these problems and proposals, a new type of database-driven expert system, Cogitator is proposed. It is shown to circumvent the Knowledge Acquisition Bottleneck and posess many other advantages over both traditional expert systems and connectionist systems, whilst having non-serious disadvantages.
机译:对建造拟人机器的追求使研究人员专注于知识及其操纵。最近,提出了一种专家系统作为解决方案,它可以在较小的,易于理解的领域中很好地工作。然而,这些最初的尝试突显了与构建系统相关的繁琐过程以显示智能,其中最引人注目的是知识获取瓶颈。试图解决此问题的尝试已导致研究人员提出使用机器学习数据库作为知识来源。尝试将数据库用作知识来源已导致开发数据库驱动的专家系统。此外,已经确定,智能系统的必要条件是强大的计算。针对这些问题和建议,提出了一种新型的数据库驱动专家系统Cogitator。它显示出绕过了知识获取瓶颈,并在传统专家系统和连接主义者系统上均具有许多其他优点,同时具有非严重的缺点。

著录项

  • 作者

    Baise Paul;

  • 作者单位
  • 年度 1994
  • 总页数
  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
  • 中图分类

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