Technology
A Theory of Heuristic Reasoning About Uncertainty
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.
A Report on FOLIO: An Expert Assistant for Portfolio Managers
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.
Communication, Simulation and Intelligent Agent:: Implications of Personal Intelligent Machines for Medical Education
To appear inProc. of the American Association for Medical Systems & Informatics, 1983 Reprinted by permission of the American Association for Medical Systems and Informatics (AAMSI). Hardware advances in the next decade promise to make poss:*ale new medical educational technologies. New media for expressing, collecting, and sharing knowledge will provide students with means for coping with the increasing amounts of information. Novel means of graphically modelling physical phenomena--providing motivating and intuitively pleasing means for explorative interaction--could complement and sometimes replace traditional text material. Intelligent programs may serve as assistants, serving roles ranging from calculator to librarian to tutor, embracing a full range of secretarial and problen solving aids.
Heuristic Programming Project 1982 Report No. HPP 82-38
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.
S Report 82-37 Computer-Based Clinical Decision Aids: Stanford KSL Some Practical Considerations. Edward
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].
GLISP: A High-Level Language for A.I. Programming
Data objects are described G1.ISP is a high-level LISP-based language which is compiled into separately from code which references the objects, making code largely LISP using a know ledge base of object descriptions. I.isp objects and representation-independent, as well as shorter and more objects in VI. representation languages are treated unifomily, this understandable. Type inference is performed when features of an makes program code independent of the data representation used, and object ap accessed, and type information is propagated by the compiler permit., changes of representation without changing code.