As a major scientific society, the AAAI has a responsibility for promoting its field as well as informing its members of the latest technical developments. Since the latter function is adequately performed by the several journals and conference proceedings already mentioned, the editorial committee chose to assign to AI Magazine the task of providing AAAI members and the public as well with a broader perspective on the research activities within AI. The approach we intend to take includes publishing informative expository and survey articles designed not so much for those working within a particular problem domain, but for those outside it who would like to gain a better understanding of the issues and methods currently being studied without having to cull all the technical literature.

Two premises, reflected in the title, underlie the perspective from which I will consider research in natural language processing in this article. First, progress on building computer systems that process natural languages in any meaningful sense (i.e., systems that interact reasonably with people in natural language) requires considering language as part of a larger communicative situation. Second, as the phrase “utterance and objective” suggests, regarding language as communication requires consideration of what is said literally, what is intended, and the relationship between the two.

The representation language used in one domain is seldom biology, management-indeed in most of the world's workthe borrowed and adapted to another, because the facilities that daily tasks are those requiring symbolic reasoning with were assets for one task become limitations elsewhere. The computers that will act this reason, most such languages are built from scratch. The as "intelligent assistants" for these professionals must be goal of the RLL effort is to reduce the amount of time RLL contains a large library of "representational pieces," for example, the mode of inheritance used by the Examples link of the Units package, or the A-Kind-Of type of Artificial Intelligence Center slot used in the MIT Frames Representation Language, FRL. Menlo Park, CA 94025 amalgamation of pieces; RLL is responsible for meshing them together into a coherent and working whole. A more advanced Peter Hart, Director user can exploit RLL's mechanisms for designing new parts, Earl Sacerdoti, Associate Director for example, a new mode of inheritance, or a new type of Charles Untulis, Assistant Director format for a slot.

The Heuristic Programming Project of the Stanford University Computer Science Department is a laboratory of about fifty people whose main goals are to model the nature of scientific reasoning processes in various types of scientific problems and various areas of science and medicine; and to construct expert systems — programs that achieve high levels of performance on tasks that normally require significant human expertise for their solution.

Over the past two years we have started a program of On the theoretical side, Professor Randall Davis has research into the development of VLSI systems. They have introduced a descriptive formalism called OMEGA, which contributes to many of the issues of Traditional automated synthesis techniques for circuit current concern in knowlege representation, and they have design are restricted to small classes of circuit functions for applied it to describe the various structured entities such as which mathematical methods exist. Sussman and his group have developed computer-aided design tools that can be of much broader assistance. Guy L. Steele developed a language to support such programming, Johan de Kleer studied causal and Professor Marvin Minsky has worked on a theory of human teleological reasoning in the recognition of circuit function thinking, which likens the mind to a society of agents and from schematics, and Howie Shrobe has worked on constraint attempts to combine a number of insights from satisfaction and the development of an interactive knowledgebased psychoanalytic, developmental, and cognitive theories of system for substantially supporting VLSI design. Further work by Richard Greenblatt and Dr. Lucia Doyle has studied belief revision via truth maintenance and Vaina develops the idea of thread memory.

The approach gives key emphasis to a succession of explicit descriptions at varying The MIT AI Laboratory has a long tradition of research in levels of visual processing, including the zero-crossing map, most aspects of Artificial Intelligence. Currently, the major foci the primal and 2'/2D sketches, and the so-called Spasar include computer vision, manipulation, learning, Englishlanguage 3D representation. Recent work has centered on directional understanding, VLSI design, expert engineering selectivity, evidence for a fifth, smaller channel for early problem solving, commonsense reasoning, computer processing, the Marr-Hildreth theory of edge detection, a architecture, distributed problem solving, models of human model of the retina, a computational theory of stereopsis and memory, programmer apprentices, and human education. Recently, Dr. Mike Brady has joined the Professor Berthold K. P. Horn and his students have studied Laboratory and has initiated a study of the psychology of intensively the image irradiance equation and its applications. The reflectance and albedo map representations have been introduced to make surface orientation, illumination geometry, and surface reflectivity explicit.

This is an excerpt from the Handbook of Artificial Intelligence, a compendium of hundreds of articles about AI ideas, techniques, and programs being prepared at Stanford University by AI researchers and students from across the country. In addition to articles describing the specifics of various AI programming methods, the Handbook contains dozens of overview articles like this one, which attempt to give historical and scientific perspective to work in the different areas of AI research. This article is from the Handbook chapter on natural language understanding. Cross-references to other articles in the handbook have been removed-terms discussed in more detail elsewhere are italicized. Many people have contributed to this chapter, including especially Anne Gardner, James Davidson, and Terry Winograd. Avron Barr and Edward A. Feigenbaum are the Handbook's general editors.

Births are always interesting affairs. According to some, births are always traumatic — a shock to come from the womb to the new world. The birth we give witness to here is that of a new society, the American Association for Artificial Intelligence — AAAI. It has not seemed to me traumatic, but rather almost wholly benign. In a world where not much is benign at the moment, such an event is devoutly to be cherished. The proper topic for this initial message is talk about beginnings and circumstances, goals and aims, character and style. My premier duty as president of AAAI, it appears, will be to give a presidential address at the upcoming annual meeting. Specific precedents being absent, I need to give thought to what belongs in an AAAI presidential address. But one thing I already know: That talk should be devoted to our science, not our society. It should be substantive , not procedural. It should look inward at the state of what we know about intelligence and computers, not outward at our place in the larger society. It is in this message that earthly matters belong.

The NLC system has grown out of an earlier series of studies on the "autoprogrammer" (Biermann[6]) and bears much resemblance to it. Program synthesis in both the current and the previous systems is based upon example calculations done by the user on displayed data structures. In the current system, the example is done in restricted English with all its power, which is a dramatic departure from the earlier approach, which simply involved pointing with a light pen. However, it is expected that many of the features from the autoprogrammer, such as "continue" and "automatic indexing", will transfer quite naturally into NLC. This paper emphasizes the natural language aspects of the system, while other reports deal with some of the additional automatic programming features. The relationship of NLC to other research in natural language processing is discussed in a later section. The next section presents an overview of NLC, after which subsequent sections discuss scanning, syntactic and semantic processing, and interpretation of commands in the "matrix computer". The next two sections discuss the processing of flow-of-control commands and the level of behavior achieved by the system. The final sections include a discussion of related research and conclusions.

The Hearsay-H speech-understanding system (SUS) developed at Carnegie-Mellon University recognizes connected speech in a 1000-word vocabulary with correct interpretations for 90 percent of test sentences. Its basic methodology involves the application of symbolic reasoning as an aid to signal processing. A marriage of general artificial intelligence techniques with specific acoustic and linguistic knowledge was needed to accomplish satisfactory speech-This research was supported chiefly by Defense Advanced Research Projects Agency contract F44620-73- C-0074 to Carnegie-Mellon University. In addition, support for the preparation of this paper was provided by USC/ISI, Rand, and the University of Massachusetts. We gratefully acknowledge their support. Views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official opinion or policy of DARPA, the U.S. government, or any other person or agency connected with them.