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Partial Evaluation, Programming Methodology, and Artificial Intelligence
This article presents a dual dependency between AI and programming methodologies. AI is an important source of ideas and tools for building sophisticated support facilities which make possible certain programming methodologies. These advanced programming methodologies in turn can have profound effects upon the methodology of AI research. Both of these dependencies are illustrated by the example of anew experimental programming methodology which is based upon current AI ideas about reasoning, representation and control. The manner in which AI systems are designed, developed and tested can be significantly improved in the programming is supported by a sufficiently powerful partial evaluator. In particular, the process of building levels of interpreters and of intertwining generate and test can be partially automated. Finally speculations about a more direct connection between AI and partial evaluation are presented.
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 ...
Letters to the Editor
Bennett, Martin, Meltzer, Bernard
The second example is of another distinguished scholar who, in a passionate contribution to the debate, stated that ... May I also take this opportunity to praise the staff Western governments, were thereby displaying a full sense of I look forward to the continuing success of the Association social responsibility, and anybody who disagreed with this in all its activities. On the surface this appears Yours sincerely, to be at least logical, until one reflects that it would not Marten E. Bennett be particularly difficult with this kind of argument to prove Gzllingham, Kent, UK that Hitler displayed a sense of social responsiblity, since one has no reason to believe that he was not sincere in believing that Jews, communists, Western capitalists and others would destroy his country if not checked. There is really not much excuse these days for anyone The background to it is the "Marietta affair." University of Cambridge, "Defended to Death," edited by movement protested on the conference site, and after some Gwyn Prins and published by Penguin Books). I came away from the meeting wondering why apparently comments.
Talking to UNIX in English: An Overview of an On-Line UNIX Consultant
The goal of the Unix Consultant is to provide a natural language help facility that allows new users to learn operating systems conventions in a relatively painless way. UC is not meant to be a substitute for a good operating system command interpreter, but rather, an additional tool at the disposal of the new user, to be used in conjunction with other operating system components.
Towards Chunking as a General Learning Mechanism
"Chunks have long been proposed as a basic organizational unit for human memory. More recently chunks have been used to model human learning on simple perceptual-motor skills. In this paper we describe recent progress in extending chunking to be a general learning mechanism by implementing it within a general problem solver. Using the Soar problem-solving architecture, we take significant steps toward a general problem solver that can learn about all aspects of its behavior. We demonstrate chunking in Soar on three tasks: the Eight Puzzle, Tic-Tat-Toe, and a part of the RI computer-configuration task. Not only is there improvement with practice, but chunking also produces significant transfer of learned behavior, and strategy acquisition."Proceedings of the AAAi-84 National Conference. AAAI, University of Texas at Austin, TX, August, 1984.
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.