In collaboration with other members of the MOLGEN project, the author developed a representation system called the "Unit Package" which became operational in July 1977. In some cases (and usually in ignorance), this work has duplicated other representation work that was happening at about the same time. The Unit Package is now being used by several other projects including two away from Stanford. It is written in INTERLISP and runs under the TENEX and TOPS20 operating systems. It is an interactive system for building knowledge-based programs. It also provides a substantial virtual memory so that knowledge bases of several thousand nodes can created without sacrificing the IlTrERLISP environment.

This paper is a "final report" on the first version of the CRYSALIS project. As such, we will summarize the current state of the system and show where we plan to go with it. We have found that a design (in the software eng ineer ing sense) is a valuable tool for the evaluation and augmentation of a program, even when the design is done ex post facto. Using such a design, we discuss the major flaws of the existing system and how to correct them. Finally, we show how the architecture of this system could be useful for certain other task domains.

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.

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.

In the early days of computing, these goals were central to the new discipline called cybernetics [126], [2]. Over the past two decades, progress toward these goals has come from a variety of fields - notably computer science, psychology, adaptive control theory, pattern recognition, and philosophy. Substantial progress has been made in developing techniques for machine learning in highly restricted environments.

Success of a knowledge-based program depends on both competence and acceptability. It must perform well for it to be worth using, but is must be acceptable to users for it to be used. There are many dimensions to developing competent and acceptable knowledge based systems which can serve as "intelligent af.sistants-for problem solvers in science (see Shortliffe and Davis, 1975). One of these is the old Al problem of representation of knowledge. Since most previous work on representation has stressed its importance for problem-solving (e.g.

Over tt7e years a range of different mechanisms have been proposed and used (e.g., standard procedure invocation, goal-directed invocation, etc.), each typically motivated by the attempt to develop new forms of knowledge encoding (e.g., procedures, PLANNER theorems, etc.). We consider in this paper tne strengths and weaknesses of a range of these mechanisms, paying particular attention to their expressiveness and validity. This analysis brings to light certain shortcomings shared to some degree by all current mechanisms. A number of ideas are presented as the basis for a mechanism which appears to offer a way of overcoming the problems discovered. We describe how those ideas have been implemented and tested in a rule-based system, and explore their impact on system performance, ease of construction, and flexibility. We consider also their value as a generalization of the existing notions of procedure calling. Though the terminology may differ, some of the shortcomings we point out and some of the ideas proposed may be recognized by others who have built similar systems, where some of these ideas have been Implemented in various Informal ways. The purpose of this paper is not, therefore, to advocate a particular solution, but instez.d

COMPUTER PROGRAM APPLIED TO INFECTIOUS DISEASES* Edward H. Shortliffe Cepartmenc of!'edicine Stanford University School of Medicine Stanford, California 94305 A rule-based expert system is described which uees artificial intellieence techniques, and a model of:he iateractica between phesiciane and human consul-:ants, to attempt to satisfy the demands of a user:o unIr7 that is often reluctant to experiment with touter zecnnology. Experteace to date has demonstrated that the program is efficient, relacively easy to use, and reliable in the domain ofbacearemei therapy selection. Future work will involve broadening dad evaluatim; tne program's expertise in other areas of infectaoue disease therapy. Ihtreductioa Few eotentialusereopulations are as demanding of tomeuter tecenology as are practicing physicians. This our to a variety of factors which include the,eysecian's independeace as a lone decision maker, the seriousaess wieh which he views actions that may often have life-and-Ceach sigaifizance, and the overwhelming:t.me

A rule-based expert system is described which uses artificial intelligence techniques, and a model of the Interaction between physicians and human consultants, to attempt to satisfy the demands of a user community that Is often reluctant to experiment with computer technology. Experience to date has demonstrated that the program Is efficient, relatively easy to use, and reliable in the domain of bacteremia therapy selection. Future work will involve broadening and evaluating the program's expertise In other areas of infectious disease thPrapy. To that end rules regarding diagnosis and treatment of meningitis have been written and are currently under evaluation.