People's certainty of the past is D follows from A. B. and C. It may be that A. B. and C, limited by the fidelity of the devices that record it, their though certain, suggest but do not confirm D. in which case knowledge of the present is always incomplete, and their the number associated with D might be less than the 1.0 that knowledge of the future is but speculation. Even though usually represents certainty in such systems. If A. B. or C nothing is certain, people behave as if almost nothing is are uncertain, then the number associated with D is modified uncertain. They are adept at discounting uncertainty -- to account for the uncertainty of its premises. These numbers making it go away. This article discusses how Al programs are given different names by different authors; we refer might be made similarly adept.

FOLIO is an expert system to assist portfolio managers. It interviews a client and, on the basis of expert knowledge, determines the client's investment goals and the portfolio that best meets them. For example, FOLIO may determine that one client requires a preponderance of tax-free investments and a substantial hedge against rising short-term interest rates, while another is best served by a mix of low-risk dividend-oriented stocks and intermediate-term bonds. FOLIO is a test bed for a theory of heuristic reasoning about uncertainty (Cohen and Grinberg, 1983), and its task has many parallels to estab!ished Al paradigms such as diagiosis in medicine and construction of a student model in ICAI domains (Barr and Feigenbaum, 1982). FOLIO uses a goal programming algorithm (Hillier and Lieberman, 190) as a relaxation method for resolving the client's multiple goals into a portfolio that fi'.s them optimally.

It has been argued that the problem of medical diagnos.r_s is fundamentally ill-structured.

John Doe - 12-34-56 Lhe patient should receive chemotherapy (PAVE-3A).

Report 82 38 The Computer and Medical Decision Making: Stanford - KSL Good Advice is Not Enough. Reprinted, with permission, from Engineering in Medicine and Biology Magazine 1,1992. Mailing address: Medical Computer Science, Room TC-117, Division of General Internal Medicine, Stanford University School of Medicine, Stanford, California 94305. Dr. Shortliffe is recipient of Research Career Development Award LM-00048 from the National Library of Medicine. Much of the training of physicians is designed to facilitate optimal, informed clinical decision making.

Medical decision making research has tended to emphasize the generation of optimal decisions, an issue which is central to the development of clinically useful consultation programs. This paper stresses the need to consider other theoretical and practical issues that are pertinent if consultation systems are to be accepted by physicians. Since adequate decision making performance remains an essential component of acceptable systems, the paper suggests c-iteria for selecting clinical problems that may be amenable to short-term implementation using state-of-the-art techniques. Introducticn At the beginning of a third decade of research into the development of computer-based diagnostic aids, it is appropriate for medical computer scientists to assess the strides that have been taken, the barriers that remain, and the optimal strategies for furthering the field in the years ahead. One purpose of this meeting is to take a thoughtful look at medical decision making research and to identify potential solutions to the theoretical and logistical problems that continue to abound [1],[2].

These diverse roles impose several requirements consultation programs has become known as »expert systems upon the system.

Report 82-33 Welcome to the MRS TUTOR!!! This tutor is designed to introduce you to the syntax and basic database accessing functions of MRS. This document is a transcript of an interaction with the MRS tutor. Reprinted by permission of the author. Funding for this work was provided by ONR Contract N00014-81-K-0004. Representation languages provide a way to store and retrieve facts from a computer. Since English is a grammatically and textually ambiguous language, representation systems use a more formal language to describe the world. The way in which the words or symbols of a language are put together to form phrases and sentences is termed the "syntax" or "grammar" of the language.

This paper describes techniques for representing control knowledge in preaicate calculus. A hybrid system is described in which metarules for diagnostic problem solving and their interpreter (both supplied by the NEOMYCIN program) are expressed in a form of predicate calculus (supplied by MRS). Procedural attachment is used to access and execute the untranslated domain knowledge. A simple deliberation/action loop manages the system at the highest level. There are three metalevels of reasoning.

The Stanford University component of this research is funded in part by ARPA contract #MDA903-80-C-0107, NIH contract # NIH RR 00785-10, ONR contract #N00014-79-C-0302. Compiled oy Bruce G. Buchanan November 1982 Abbreviations Used in This Bibliography: AAAI American Association for An:ficial Intelligence ACM Association for Computing Machinery AFIPS American Federation of Information Processing Societies ECAI European Conference on Artificial Intelligence IEEE Institute for Electrical and Electronic Engineers IFIPS International Federation of Information Processing Societies IJCAI International Joint Cr nferences on Artificial Intelligence SIGPLAN ACM Specia! Abe, N., ltoh, F., and Tsuji, S. Toward a learning of object models using analogical objects and verbal instruction. Addis, T. R., and Hartley, R. T. A faultfinding aid u,sing a content addressable file store. ICL Technical Note TN 79, ICL Ltd., London, 1979.