R.M.BURSTALL 373 23 Assertions: programs written without specifying unnecessary order.

J. P. Thorne Department of English Language P. Bratley and H. Dewar Department of Computer Science University of Edinburgh 1. INTRODUCTION In this paper we describe a program which will assign deep and surface structure analyses to an infinite number of English sentences.1 The design of this program differs in several respects from that of other automatic parsers presently in existence. All these differences are a consequence of the particular aim we have pursued in writing the program, which represents an attempt to construct a device that will not only assign a syntactic analysis to any English sentence-that is, a record of the syntactic structure that the native speaker Perceives in any English sentence-but which also, to some extent, simulates the way in which he perceives this structure. This is not to say that the analyzer differs from others because we have based its design upon the findings of psycholinguistic experiments. For one thing very few experiments on the perception of syntactic structure have been carried out and for the most part the results have been fairly inconclusive. But it is the case that we have, as far as possible, treated the task of constructing an automatic parser as being itself a psycholinguistic experiment. That is to say, any proposal regarding the possible operation of the program has been judged (mainly as the result of introspection) according to whether or not it seemed to be consistent with human behaviour. And this has led to our incorporating certain features which are absent from other automatic parsing systems. Among the most notable of these features is the program's ability to assign syntactic labels to an infinite number of words while operating with a finite dictionary. As far as we know, all other automatic parsers of English (or 1 This work was supported by the Office for Scientific and Technical Information Grant No. ID/102/2/06 to Professor Angus McIntosh.

Networks as models of word storage: G. R. Kiss

RELATION TO PHYSIOLOGY It is possible to compare the organisation of this system with the organisation of the visual system, as revealed by microelectrode studies in the cat (Hubel & Wiesel 1962, 1965) and the frog (Lettvin, Maturana, McCulloch & Pitts 1959). Briefly the following points emerge: (1) Cells in the visual cortex only respond to local properties of the visual scene, e.g., edges, line segments. This mirrors the immediate constituent constraint imposed for economic reasons in the picture grammar.

Psychological theory attempts to explain how thinking--the subject matter of psychology--is possible by a brain composed of single mechanistic elements--the basic assumption of psychology. The problem of programming digital computers to behave in complex fashions is equivalent to this aspect of the psychological problem. Today automata theorists agree that no fundamental barrier blocks the development of machines which can think, by any reasonable definition of the term. However, the precise techniques for implementing general thinking proceGseE-J have been only partially developed. An example of a high-level, general thinking process is comprehension: the understanding of passages of a natural language.

This report presents BAOBAB-2, a computer program built upon MYCIN [Shortliffe, 1974] that Is used for understanding medical summaries describing the status of patients. Due both to the conventional way physicians present medical problems In these summaries and the constrained nature of medical jargon, these texts have a very strong structure. BAOBAB-2 takes advantage of this structure by using a model of this organization as a set of related schemes 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 are discussed.

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.