Government
Introduction to the COMTEX Microfiche Edition of the SRI Artificial Intelligence Center: Technical Notes
Charles A. Rosen came to SRI in 1957. I arrived in 1961. Between these dates, Charlie organized an Applied Physics Laboratory and became interested in "learning machines" and "self-organizing systems." That interest launched a group that ultimately grew into a major world center of artificial intelligence research - a center that has endured twenty-five years of boom and bust in fashion, has "graduated" over a hundred AI research professionals, and has generated ideas and programs resulting in new products and companies as well as scientific articles, books, and this particular collection itself.
Artificial Intelligence Research at the University of Maryland
The University of Maryland's Computer Science Department conducts a broad research program in both theoretical and applied artificial intelligence. Nine faculty and more than fifty research associates and graduate students are involved in AI research. Projects are funded by a large number of government agencies, as well as by several major corporations. The computing environment will improve dramatically over the next several years, due in large part to Coordinated Experimental Research Department by the National Science Foundation in 1982. In addition to the research program in AI, the Department offers a large number of courses at both the graduate and undergraduate levels on all facets of AI. The principal AI laboratories also sponsor numerous colloquia by visiting scientists and permanent laboratory personnel. The principal research areas are computer vision, search and decision making, parallel problems solving, and database research.
Alexander Lerner: A Biographical Sketch
In 1939, he defended a thesis on a new method of calculating A special session entitled "Future Directions In Artificial He was awarded the title Candidate of Intelligence in Washington, D.C. in August. The session, Technical Sciences by the Moscow Institute of Energetics, chaired by Jack Minker, was held to honor Soviet cyberneticist where he worked as a lecturer until the USSR entered World Alexander Yankelovich Lerner's seventieth birthday. He was then commissioned to work at an iron and Minker described Dr. Lerner's contributions to science. The two years of practical work at the Patrick Winston gave a technical presentation, followed by plant led to his book Construction of Industraal Automatic questions from the audience. Electrzcal Drives, published in 1950, together with E.A. Following the session, 228 attendees signed a letter wishing Rosenman. After the war he was appointed head of the Dr. Lerner a happy birthday, and 233 attendees signed USSR's newly established Central ...
Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project
Buchanan, Bruce G., Shortliffe, Edward H.
Artificial intelligence, or AI, is largely an experimental science—at least as much progress has been made by building and analyzing programs as by examining theoretical questions. MYCIN is one of several well-known programs that embody some intelligence and provide data on the extent to which intelligent behavior can be programmed. As with other AI programs, its development was slow and not always in a forward direction. But we feel we learned some useful lessons in the course of nearly a decade of work on MYCIN and related programs. In this book we share the results of many experiments performed in that time, and we try to paint a coherent picture of the work. The book is intended to be a critical analysis of several pieces of related research, performed by a large number of scientists. We believe that the whole field of AI will benefit from such attempts to take a detailed retrospective look at experiments, for in this way the scientific foundations of the field will gradually be defined. It is for all these reasons that we have prepared this analysis of the MYCIN experiments.
The complete book in a single file.
What Should Artificial Intelligence Want from the Supercomputers?
While some proposals for supercomputers increase the powers of existing machines like CDC and Cray supercomputers, others suggest radical changes of architecture to speed up non-traditional operations such as logical inference in PROLOG, recognition/ action in production systems, or message passing. We examine the case of parallel PROLOG to identify several related computations which subsume those of parallel PROLOG, but which have much wider interest, and which may have roughly the same difficulty of mechanization. Similar considerations apply to some other proposed architectures as well, raising the possibility that current efforts may be limiting their aims unnecessarily.
GLISP: A Lisp-Based Programming System with Data Abstraction
GLISP is a high-level language that is complied into LISP. It provides a versatile abstract-data-type facility with hierarchical inheritance of properties and object-centered programming. GLISP programs are shorter and more readable than equivalent LISP programs. The object code produced by GLISP is optimized, making it about as efficient as handwritten Lisp. An integrated programming environment is provided, including automatic incremental compilation, interpretive programming features, and an intelligent display-based inspector/editor for data and data-type descriptions. GLISP code is relatively portable; the compiler and data inspector are implemented for most major dialects of LISP and are available free or at nominal cost.
Methodological Simplicity in Expert System Construction: The Case of Judgments and Reasoned Assumptions
Editors' Note: Many expert systems require some means criticisms of this approach from those steeped in the practical of handling heuristic rules whose conclusions are less than certain issues of constructing large rule-based expert systems. Abstract the expert system draws inferences in solving different problems. Doyle's paper argues that it is difficult for a human expert "certainty factors," and in spite of the experimentally observed insensitivity of system performance to perturbations of the chosen values Recent successes of "expert systems" stem from much Research Projects Agency (DOD), ARPA Order No. 3597, monitored In the following, we explain the modified approach together with its practical and theoretical attractions. The client's income bracket is 50%, can be found (Minsky, 1975; Shortliffe & Buchanan, 1975; and 2. The client carefully studies market trends, Duda, Hart, & Nilsson, 1976; Szolovits, 1978; Szolovits & THEN: 3. There is evidence (0.8) that the investment Pauker, 1978). Reasoned Assumptions (from Davis, 1979) and would use the rule to draw conclusions whose "certainty factors" depend on the observed certainty Although our approach usually approximates that of Bayesian probabilities, accommodates representational systems based on "frames" namely as subjective degrees of belief.
Artificial Intelligence Research at the Artificial Intelligence Laboratory, Massachusetts Institute of Technology
The primary goal of the Artificial Intelligence Laboratory is to understand how computers can be made to exhibit intelligence. Two corollary goals are to make computers more useful and to understand certain aspects of human intelligence. Current research includes work on computer robotics and vision, expert systems, learning and commonsense reasoning, natural language understanding, and computer architecture.
The Banishment of Paper-Work
It may come as a surprise to some to be told that the modern digital computer is really quite old in concept, and the year 1984 will be celebrated as the 150th anniversary of the invention of the first computer the Analytical Engine of the Englishman Charles Babbage. One hundred and fifty years is really quite a long period of time in terms of modern science and industry and, at first glance, it seems unduly long for new concept to come into full fruition. Unfortunately, Charles Babbage was ahead of his time, and it took one hundred years of technical development, the impetus of the second World War and the perception of John Von Neumann to bring the computer into being. Now twenty years later and with several generations of computer behind us, we are in a position to make a somewhat more meaningful prognosis than appeared possible in, say 1948. We can only hope that we will not be as far off actuality as we believe George Orwell to be, or as far off in our time scale as were Charles Babbage and his almost equally famous interpreter, Lady Lovelace.