THEORETICAL INVESTIGATION OF THE LIMITS OF AI AND KNOWLEDGE REPRESENTATION

知识表示是人工智能关注的一个基本问题 研究并引发了如何 在计算机中高效地表示知识。我们认为 各方面的问题，并找出了关键 值得关注的是，任何适用于大型 文本数据库必须处理 1)没有实用的知识表示系统 此时开发的，允许转换为 将大量的文本转换为机器可读的形式。这 将需要一个语言理解的解决方案 有问题。这个问题目前显然还没有得到解决。 2)知识表示有理论上的局限性 它必须基于人类已知的局限性而存在 自然语言口译方面的表现。这些限制 让期待机器解决方案变得不合理，除非我们 可以用一台比它更好的机器来实现性能 像人类一样。 调查访问权限限制的下一步是 大型数据库中的文本数据是我们的一项研究 建议审查学科知识在人类中的作用 对文档对的相关性进行评级时的表现。我们有 已经积累了人类对两个问题的多重判断 不同的文档对测试集。评委们都是 在一定程度上了解该领域知识的人。我们现在是 一项研究大约进行了一半，该研究试图 更好地理解人类判断过程的本质。 一些精通英语的法官，但谁是 专业领域与分子生物学无关，是 现在正在执行判决任务。结果将使 这是一个有用的比较，有助于描述 让知识接受判断。我们的目标是更好地 了解人类如何在选择文档时使用知识 以满足特定的需求。

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 test sets of document pairs. The judges were all people knowledgeable in the field at some level. We are now approximately half way through a study which seeks to understand better the nature of the human judgment process. A number of judges who are literate in English, but who's area of expertise is not related to molecular biology, are now carrying out 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.