作业帮英语翻译Expert systems represent knowledge in sets of ‘if-then-e
来源：学生作业帮 编辑：作业帮 分类：英语作业 时间：2024/05/17 23:14:58
英语翻译
Expert systems represent knowledge in sets of ‘if-then-else’ rules.Propositions are proven by discovering a chain of rules.This may be done through either forward or backward chaining.In forward chaining.Expert systems have had a measure of success on certain well-defined probllsms.There have,however,been many
failures.Most of the problems have arisen from the difficulty of obtaining a consistent,complete set of rules.The rule acquisition process requires the interaction of two specialists:a knowledge engineer and a domain expert.There are several problems with this process.First,the domain experts may not be fully co-operative.After all,they are being asked to participate in the development of a
system that will replace them with a computer.More often,domain experts only appear to be unco-operative; they simply cannot create a set of rules that explain how certain things are done.From one point of view,only trivial things can be reduced to a set of rules;all important aspects of human intelligence are beyond a simple rule set because a human expert’s knowledge is often in the form of natural language with imprecision or vague information.
对不起，是翻译成中文。
Expert systems represent knowledge in sets of ‘if-then-else’ rules.Propositions are proven by discovering a chain of rules.This may be done through either forward or backward chaining.In forward chaining.Expert systems have had a measure of success on certain well-defined probllsms.There have,however,been many
failures.Most of the problems have arisen from the difficulty of obtaining a consistent,complete set of rules.The rule acquisition process requires the interaction of two specialists:a knowledge engineer and a domain expert.There are several problems with this process.First,the domain experts may not be fully co-operative.After all,they are being asked to participate in the development of a
system that will replace them with a computer.More often,domain experts only appear to be unco-operative; they simply cannot create a set of rules that explain how certain things are done.From one point of view,only trivial things can be reduced to a set of rules;all important aspects of human intelligence are beyond a simple rule set because a human expert’s knowledge is often in the form of natural language with imprecision or vague information.
对不起，是翻译成中文。
这篇难度中上,内容挺有意思.可惜楼上都有机译对付了.相信你对我的指导译文满意：
专家系统通过‘如果-那么-不然’这组规则来代表知识.命题通过发现一连串规则来发现.这可以通过前进或后退链.在向前链,专家系统在处理若干明确界定的问题方面,获得了一定程度的成功.不过,也遭遇过很多失败.
system that will replace them大多数的问题源于难以获得一套一致、完整的规则.规则采集过程中需要两位专家的相互作用:一名知识工程师和一名地域专家.在这一过程中会有几个问题.第一,地域专家不一定充分合作.毕竟,是在要求地域专家参与研究开发一个要用计算机取代他们的系统.领域专家们往往显得持不合作的太多；他们简直就不能创造出一套规则解释若干事情是怎么办的.从一个观点来看,只有鸡毛蒜皮的小事也能被归纳为一套规则,人类智慧的所有重要方面是不能用一套简单的规则来表示的,因为作为人的专家知识经常是以自然语言表现的,里面包含着不精确性或含糊不清的信息.
专家系统通过‘如果-那么-不然’这组规则来代表知识.命题通过发现一连串规则来发现.这可以通过前进或后退链.在向前链,专家系统在处理若干明确界定的问题方面,获得了一定程度的成功.不过,也遭遇过很多失败.
system that will replace them大多数的问题源于难以获得一套一致、完整的规则.规则采集过程中需要两位专家的相互作用:一名知识工程师和一名地域专家.在这一过程中会有几个问题.第一,地域专家不一定充分合作.毕竟,是在要求地域专家参与研究开发一个要用计算机取代他们的系统.领域专家们往往显得持不合作的太多；他们简直就不能创造出一套规则解释若干事情是怎么办的.从一个观点来看,只有鸡毛蒜皮的小事也能被归纳为一套规则,人类智慧的所有重要方面是不能用一套简单的规则来表示的,因为作为人的专家知识经常是以自然语言表现的,里面包含着不精确性或含糊不清的信息.
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