Theorem Proving Vision Robotics Information Processing Psychology Learning and Inductive Inference Planning and Related Problem-solving Techniques A. Natural Language Processing Ovnrview The most common way that human beings communicate Is by speaking or writing In one of the "natural" languages, like English, French, or Chinese. Computer programming languages, on the other hand, seem awkward to humans. These "artificial" languages are designed to have a rigid format, or syntax, so that a computer program reading and compiling code written In an artificial language can understand what the programmer means. In addition to being structurally simpler than natural languages, the artificial languages can express easily only those concepts that are important In programming: "Do this then do that," "See it such and such Is true," etc. The things that can be expressed In a language are referred to as the semantics of the language. The research on understanding natural language described in this section of the Handbook is concerned with programs that deal with the full range of meaning of languages like English.

Those of us involved In the creation of the Handbook of Artificial Intelligence, both writers and editors, have attempted to make the concepts, methods, tools, and main results of artificial Intelligence research accessible to a broad scientific and engineering audience. Currently, Al work Is familiar mainly to its practicing specialists and other interested computer scientists. Yet the field Is of growing interdisciplinary interest and practical Importance. With this book we are trying to build bridges that are easily crossed by engineers, scientists in other fields, and our own computer science colleagues. In the Handbook we Intend to cover the breadth and depth of Al, presenting general overviews of the scientific issues, as well as detailed discussions of particular to -hniques and Important Al systems.

This pc)er presents BAOBAB-2, a computer program built around MYCIN [Shortliff e, 1974] that is used for understanding medical summaries describing the status of patients. Due to the stereotypic way the physicians present medical problems in these summaries in addition to the constrained nature of medical jargon, these texts have a very strong structure. BAOBAB-2 takes advantage of these structures by having a model of this organization as a set of related schemas that facilitate the interpretation of these texts. Structures of the schemes and their relation to the surface structure are described. Issues relating to selection and use of these schemes by the program during Interpretation of the summaries ara discussed.

This is traditionally done with tne aid of a computer programmer acting as intermediary. The dire_t transfer of knowledge from an expert to the system requires a natural-language processor capable of handling a substantial subset of English. The development of such a natural-language processor is a long-term goal of automating knowledge acquisition; faciliting the interface between the expert and the system is a first step toward this goal. This paper describes BAUBAb, a program designed and implemented for hYCIN (Shortliffe 1974), a medical consultation system for infectious disease diagnosis and therapy selection. EAUdAb is concerned with the problem of parsing - recognizing natural language sentences aad encoding tnem into MICIN's internal representation. For this purpose, it uses a semantic grammar in whicft tne non-terminal symools denote semantic categories (e.g., infections and symptoms), or conceptual categories wnicn are common tools of knowledge representation in artificial intelligence (e.g.

Shortly after Watson and Crick's discovery of the structure of DNA, and at about the same time that the genetic code and the essential facts of gene expression were being elucidated, the field of linguistics was being similarly revolutionized by the work of Noam Chomsky [Chomsky, 1955, 1957, 1959, 1963, 1965]. Observing that a seemingly infinite variety of language was available to individual human beings based on clearly finite resources and experience, he proposed a formal representation of the rules or syntax of language, called generative grammar, that could provide finite--indeed, concise--characterizations of such infinite languages. Just as the breakthroughs in molecular biology in that era served to anchor genetic concepts in physical structures and opened up entirely novel experimental paradigms, so did Chomsky's insight serve to energize the field of linguistics, with putative correlates of cognitive processes that could for the first time be reasoned about 48 A

Participants in the search for intelligent machines frequently disagree on a basic question of strategy in their quest. On the one hand there are those who believe that the major obstacles can be overcome by reliance on the computer's infallible memory, electronic speed, and arithmetic capabilities uig This report takes the position that immediate, practical applica can derive from the former approach, but the major problems will be "\ To mention a single example, the implementation f information retrieval techniques on present-day computers would be a large step forward, even though the techniques thus far considered have largely been conceptually trivial. Luhn (1958) has u sed a straightforward statistical procedure to extract key sentences from scientific articles, thus yielding useful abstracts of a sort. For even an unintelligent human does more than count frequencies or search for key words. The human displays intelligent features which are generally summed up by saying that he ...

Baseball is a first step toward this goal.

Methods of Approach At the outset it might be well to distinguish sharply between two general approaches to the problem of machine learning.

The editors have provided him with special introductory sections as a ing guide to a thorough understand of the reports.

When working from of a small set of primitives and the statement of a such representations, lexical choice is often a nonissue program's knowledge as a set of expressions over these since each term can be uniquely associated with a natural primitives plus a set of constant terms for individuals.