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第一代专家系统已经表明人工智能(AI)技术能够用于解决各种特定领域里的问题.解决这些问题通常需要人们多年来积累的经验知识.不过,尽管这些系统具有实在的能力,但它们解决的问题范围受到严格的限制.未来几年内关于专家系统的工作,在某种程度上肯定将集中到扩大范围而又不牺牲能力的方面.本文力图说明一种有希望通往上述目的之途径.它包括首先更好地理解在不同领域内行之有效的各种问题求解方法,而后借助于这种理解来开发更好的知识获取工具,最终开发出具有从总体上比现有专家系统解题范围更宽的协同式问题求解器.
The first generation of expert systems has shown that artificial intelligence (AI) technology can be used to solve problems in a variety of specific areas, and solving them often requires empirical knowledge that people have accumulated over the years, but despite their real capabilities, The scope of the problem to be solved is severely limited, and in the coming years the work on an expert system, to a certain extent, will certainly be focused on expanding the area without sacrificing capacity.This article seeks to exemplify a promising route to that end It consists of a better understanding of the various problem solving methods that work well in different fields and the development of better knowledge acquisition tools with the aid of this understanding and ultimately the development of tools that have the overall problem of overcoming problems with existing expert systems A wider range of cooperative problem solvers.