THEORECTICAL INVESTIGATION OF THE LIMITS OF AI AND KNOWLEDGE REPRESENTATION

知识表示是人工智能研究的一个基本问题， 这就产生了如何有效地表示知识的子问题 在电脑里 我们考虑了问题的各个方面， 确定了任何适用于大型企业的实际系统所关注的关键问题， 文本数据库必须处理 1)目前还没有开发出实用的知识表示系统， 这一次，它允许大量的文本转换为机器 可读形式。 这就需要解决语言问题 理解问题。 这显然是没有解决在这个时候。 2)知识表示存在理论限制，必须 存在的依据是人类在口译中表现出的已知局限性 自然语言 这些限制使得期望一台机器 除非我们能用一台性能上级 一个人类的。 在调查访问文本数据的限制时， 一个大型数据库是我们提出的一项研究， 对文档对进行评级时人因绩效的主题知识 本案无关 我们已经积累了多个人类判断， 两个不同的文档对测试集。 评委们都是 在某种程度上，他在这个领域很有知识。 现在的建议是， 一些法官谁是识字的英语，但谁的领域， 专业知识与分子生物学无关，重复判断任务。 结果将进行有用的比较，以帮助描绘 学科知识对判断的贡献 我们的目标是更好地 了解人类如何使用知识来选择文档，以满足 定义的需要。

Knowledge representation is a fundamental concern of AI research and has given rise to the subproblem of how to efficiently represent knowledge in a computer. We consider various aspects of the problem and have identified key concerns which any practical system applicable to large textual databases must deal with 1) No practical knowledge representation system has been developed at this time which allows the conversion of large amounts of text to machine readable form. This would require a solution to the language understanding problem. This is clearly not solved at this time. 2) There are theoretical limits to knowledge representation that must exist based on known limitations of human performance in interpreting natural language. These limits make it unreasonable to expect a machine solution unless we can achieve a performance with a machine superior to that of a human. The next step in investigating the limits of access to textual data in a large database is a study we have proposed to examine the role of subject knowledge in human performance at rating document pairs for relevance. We have already accumulated multiple human judgments made on two different tests sets of document pairs. The judges were all people knowledgeable in the field at some level. The proposal now is to have a number of judges who are literate in English, but who's area of expertise is not related to molecular biology, repeat the judgment task. The results will make a useful comparison to help delineate the contribution of subject knowledge to judgments. The goal is to better understand how humans use knowledge in selecting documents to meet a defined need.