Theorem Proving Vision Robotics Information Processing Psychology Learning and Inductive Inference Planning and Related Problem-solving Techniques Automatic Programming (AP) Is a new, dynamic, and not precisely defined area of artificial intelligence. This overview discusses the definitions, history, motivating forces and goals of automatic programming and includes a brief description of the basic characteristics and central issues of AP systems. The article begins with a section discussing the various possible definitions of automatic programming, the background in which it has achieved existence, as well as some of its general motivating forces and goals. The next section describes four characteristics of all AP systems: the method by which a user of such a system specifies or describes the desired program, the target language in which the system writes the program, the problem or application area to which the system is addressed, and the approach or operational method employed by the system. Next, a section discusses four basic issues, one or more of which concern all AP systems: the representation and processing of partial or incomplete information; the transformation of structures, and especially the transformation of program descriptions into other descriptions (in this chapter, the term program description includes the user's specification of the desired program, any Internal representations of the progrrm, as well as the target language implementation); the efficiency of the target language Imp,ementation; and the system's capabilities for aiding in the understanding of the program.

Theorem Proving Vision Robotics Information Processing Psychology Learning and Inductive Inference Planning and Related Problem-solving Techniques A. Overview There are two main area.

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.

We have developed and partially Imp;zmented an "automated consultant" called SACON (Structural Analysis CONsultant), using the EMYCIN system as Its framework. SACON advises non expert engineers in the use of a large, general-purpose structural analysis program. The structure of the knowledge b,:se, including the major concepts used and Inferences drawn by the consultant, is presented. We conclude by making some observations 11 light of this application about the EMYCIN system as a representational vehicle and the process of acquiring knowledge for rule-based systems. Key words: knowledge-based systems, knowledge acquisition, knowledge representation, automated consultant, structural analysis, inference structure. This research was supported by the Defense Advanced Research Projects Agency (ARPA Order No. 2494 Contract No. DAHC15-73-C-0435) and the Air Force Flight Dynamics Laboratory. Reprinted from the Sixth International Joint Conference on Artificial Intelligence, Tokyo, Japan, August 1979. Used by permission of the International Joint Conference on Artificial Intelligence, Inc.; copies of the Proceedings are available from Morgan Kaufmann Publishers, Inc., 95 First Street, Los Altos, CA 94022, USA.

AGE is a system designed to aid knowledge engineers build knowledge-based programs. We have built a laboratory of building blocks which the user can assemble in various ways to fit a particular problem. This paper describes the facilities available to the user and descibes an example program built with AGE.

The performance of a computer-based clinical consultation system is evaluated. The program, called MYCIN, is designed to function as an aid for infectious disease diagnosis are therapy selection, with an initial emphasis on bacteremias. The evaluation methodology is discussed, as well as the difficulties encountered in attempting to evaluate clinical judgments. Specialists in infectious diseases judged MYCIN's final therapy recommendation, and intermediate conclusions about the significance of the infection and identity of infecting organisms. The evaluation techniques described may be useful in assessing the performance of other clinical decision aids. Results of the evaluation show that the program's therapy recommendations meet Stanford experts' standards of acceptable practice 90.9% of the time (Table II), with some variation noted both among individual experts and between Stanford experts and others (Tables I and II).

We view this process as occurring in several stages, which together form a data hierarchy (Figure 3.1). The hierarchy offers an overview of DSS function and suggests a task partitioning suitable for a contract net approach.

The discussion centers on a specific video terminal designed and constructed by the authors. This terminal is based on the Intel 8080 microprocessor and is equipped with software sufficient to emiflate the characteristics of standard video terminals required by eral available screen -oriented text editors in common use at sites throughout the ARPAnet (such as E [Samuel, 1978] and TV-Edit [kanerva, 1975]). Screen-oriented editors2 differ from other editors In their use of high-speed video terminals to display the contents of large sections of a file being edited. As editing operations are performed, the display Is revised to indicate their effects on the file (i.e., editing operates In a What you see is what you get mode). Such editors require ter.linals capable of primitive text-processing operations, such as inserting a character in a line of text by shifting the existing characters. In addition to such capabilities, the terminal is typically expected to support 8-bit transmission (instead of the usual 7 bits plus parity), selectable modes for displaying characters (e.g., normal or inverse video, blinking, or dual intensity), and an 80-character line width.

ABSTReCT The research activities of the Heuristic Programming Project, for the four-year period ending July 31, 1977, are summarized in this report. Contributions to Knowledge Engineering research in the fields of knowledge acquisition (both interactive and automated), knowledge representation and knowledge utilization were reported in over thirty publications by members of the project. A summary of those publications is?resented here. The Al Handbook, an encyclopedic reference to the field of::tificial Intelligence, is described in the appendix, along with the excecteç table of contents and sample articles.