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    Artificial Intelligence and Cybernetics

    George Washington University
    Course ID Management 265
    Department of Management Science
    Spring 1990
    Paul Pangaro, Instructor

    [The following text and figure constituted a course description taught to approximately 25 students. Some colleagues upon hearing of this activity dubbed the course title, "AI versus Cybernetics."]

    Artificial Intelligence and Cybernetics: Aren't they the same thing? Isn't one just about computers and the other about robots? The answer to these questions is emphatically, No.



    The field of Artificial Intelligence (AI) came into being when concepts of universal computation, the brain as computer, and digital computing were combined. Fundamentally concerned with demonstration and application, AI moved inevitably to assume the challenge of reproducing and/or explaining human mentation, problem solving and language. It stands today as a major influence on the fields of biology, cognitive and computation science, and epistemology.

    The field of Cybernetics came into being when concepts of information, feedback and control were generalized from specific applications to systems in general, including systems of living organisms, systems of self-reference and systems of language. Fundamentally an applied philosophy, cybernetics has taken on problems of subjectivity in science while still addressing how to make intelligent artifacts. It stands today as a major influence on biology, cognitive and computation science, and epistemology.

    Ironically but logically, AI and Cybernetics have each gone in and out of fashion and influence. Cybernetics started a bit in advance of AI, but AI has dominated for the last 25 years. Now recent difficulties in AI have led to renewed search for solutions that mirror the past approaches of Cybernetics. In this course, the distinct roots and applications of each field will be studied, and the implications of their future influences will be explored.

    The objectives of the course are to provide:
    1. Knowledge of the history of AI and Cybernetics from the contexts in which they evolved and continue to flourish, as well as an understanding of their similarities and differences
    2. Understanding of their approach to the concepts of, and their embodiments for, information, representation of the world, knowing, learning and language
    3. Awareness of specific applications of AI and Cybernetics, in areas of machine learning, knowledge representation, decision aides, intelligent training, hypermedia, groupware and neural nets
    4. An opportunity to project how each field might approach specific new applications and its possible success.
    Course Requirements
    1. Term paper of 15 to 20 double-spaced, typewritten pages, due on the next-to-last day of class. (By special arrangement with the instructor, a software demonstration can be substituted.) A one-paragraph statement of the topic is due at the fifth class. A rough draft of the major argument of the paper (at least half the length of the final) is due at the ninth class.
    2. A series of 3 (or more) short articles of 1 to 4 double-spaced, typewritten pages on topics that interest you during the course. One is due at the fourth class, another at the eight and another at twelfth.
    3. A short presentation to the class of some 15 minutes on a topic from the term paper or short article. Dates will be arranged during the term.
    Required Texts
    • Pylyshyn, Zenon W. THE ROBOT'S DILEMMA, Ablex Publishing, 1987.
    • Winograd & Flores, UNDERSTANDING COMPUTERS AND COGNITION, Ablex Publishing, 1986.
    • Dreyfus & Dreyfus, MIND OVER MACHINE. Free Press, 1986.
    Other required papers and suggested readings to be assigned during the semester.

    - end-

    Related Course:

    Introduction to Systems Science and Cybernetics, The George Washington University, Fall 1990




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