代表性的变化是推理的组成部分
Alan Bundy1, Xue Li1
1School of Informatics, University of Edinburgh, Edinburgh, UK.
概括
人类的推理往往会改变现有的知识表示,而不仅仅是添加新的信息. 本研究介绍了ABC系统,用于自动化认知人工智能中的表示变化.
科学领域:
- 认知科学 认知科学
- 人工智能的人工智能
- 科学哲学的科学哲学
背景情况:
- 推理涉及从现有的表征中获得新的知识.
- 知识的表现在推理过程中演变,而不仅仅是通过加法.
- 在AI和认知科学中,推理对知识表示的影响一直被忽视.
研究的目的:
- 突出代表性变化的意义,作为推理的副作用.
- 分析Imre Lakatos关于数学方法演变的研究作为一个案例研究.
- 引入和验证用于自动化表示变化的计算系统.
主要方法:
- 分析Imre Lakatos理性重建的数学方法的分析.
- 绑架,信念修订和概念变化 (ABC) 理论修复系统的描述.
- 展示ABC系统在自动化表示变更方面的能力.
主要成果:
- 人类的推理经常修改现有的知识表示.
- 该ABC系统有效地自动化了表示变化的过程.
- 在各种应用中,ABC系统显示出修复错误的知识表示的潜力.
结论:
- 代表性变化是推理的一个至关重要的,但未被充分研究的方面.
- 该ABC系统提供了一个计算方法来解决AI中的表示演变.
- 自动化表示变化对认知人工智能有广泛的影响.
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