Introduction to knowledge-based systems
Introduction to knowledge-based systems
复制标题
基于知识的系统简介
DOI：
10.1109/etd.1995.403493
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发表时间：
1995
期刊：
影响因子：
--
通讯作者：
L. Jain
中科院分区：
文献类型：
--
作者：
L. Jain
在过去十年左右的时间里，专家系统也被称为基于知识的系统，它们已经从研究实验室进入了现实世界。在商业、医学、制造、国防、天文、科学和工程等不同领域，已经并将继续开发应用程序。这类应用程序执行的任务包括解释、预测、诊断、设计、规划、监控、调试、修复、指令和控制。专家系统是人工智能的分支，人工智能关注的是使用计算机以有限的方式模拟人类的智能。一些研究人员将人工智能(AI)定义为让机器做一些如果由人类完成则需要智能的事情的科学。在过去的几十年里，人工智能已经扩展到主要的子领域，包括专家系统、人工神经网络、模糊系统、进化计算和混沌理论。一些研究人员不区分专家系统和基于知识的系统。所有这些发展背后的关键问题是知识获取、知识表示和知识处理。
In the last decade or so, expert systems also called knowledge-based systems have made their way from research laboratories into the real world. Applications have been, and are continuing to be, developed in areas as diverse as business, medicine, manufacturing, defence, astronomy, science and engineering. Such applications perform tasks that include interpretation, prediction, diagnosis, design, planning, monitoring, debugging, repairing, instruction and control. The expert systems are the offshoots of artificial intelligence which is concerned with using computers to simulate human intelligence in a limited way. Some researchers define artificial intelligence (AI) as the science of making machines do things that would require intelligence if done by men. In the last few decades, AI has spread into major subfields including expert systems, artificial neural networks, fuzzy systems, evolutionary computation and chaos theory. Some researchers do not differentiate between expert systems and knowledge-based systems. The key issue behind all these developments is the knowledge acquisition, knowledge representation and knowledge processing.<<ETX>>