人工智能中机器学习的研究与应用

Ming Xue, Chang-jun Zhu
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引用次数: 54

摘要

本文阐述了机器学习的概念、意义和主要策略,以及机器学习系统的基本结构。结合主要策略的几个基本思想,重点介绍了几种机器学习方法,如死记硬背学习、基于解释的学习、根据指导学习、通过演绎学习、通过类比学习和归纳学习等。同时,对它们各自的优势和局限性进行了比较分析。文章最后提出了机器学习的研究目标,并指出了机器学习的发展趋势。机器学习是使计算机具有智能的基本方法;它的应用主要是归纳法和综合法,而不是演绎法,已经扩展到人工智能的许多领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Study and Application on Machine Learning of Artificial Intellligence
This thesis elaborated the concept, significance and main strategy of machine learning as well as the basic structure of machine learning system. By combining several basic ideas of main strategies, great effort are laid on introducing several machine learning methods, such as Rote learning, Explanation-based learning, Learning from instruction, Learning by deduction, Learning by analogy and Inductive learning, etc. Meanwhile, comparison and analysis are made upon their respective advantages and limitations. At the end of the article, it proposes the research objective of machine learning and points out its development trend.Machine learning is a fundamental way that enable the computer to have the intelligence ; Its application which had been used mainly the method of induction and the synthesis¿rather than the deduction has already reached many fields of Artificial Intelligence.
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