EngrI/CS 172 : Computation, Information, and
Intelligence, Fall 2001
Click here for the most
current version of the course
Knowledge without appropriate procedures for
its use is dumb, and procedure without suitable knowledge is blind.
-- Herb Simon, "Artificial Intelligence Systems
that Understand", 1977.
Epigraph runner-ups:
In the world of systems design, programs and data are the scissor
blades working together to form the broader class -- software. Lacking
either blade, computers couldn't cut through problems -- yet for many people,
"software" is synonymous with "programs".
--Tom Gilb and Gerald M. Weinberg, Humanized Input: Techniques for
Reliable Keyed Input, 1977
There is a sense in which the study of machine intelligence can be described
as the application of philosophy to technology.
--Donald Michie, Machine Intelligence and Related Topics: An Information
Scientist's Weekend Book, 1982.
Final and course grades were posted on
the door of Upson 4152 at 10pm Tuesday 12/18/01. Course policy is
that information about grades, means, etc. cannot be posted on the web
or given through email. Final exams can be viewed by appointment.
An introduction to computer science using techniques and examples from
the field of artificial intelligence. Topics include compute-intensive
methods, search techniques, game playing, natural language processing,
data mining, the World Wide Web, information retrieval, learning theory,
machine translation, the Turing test. This is not a programming course.
Course work will include "pencil and paper" problem solving assignments.
Course Staff
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Prof. Lillian Lee, 4152
Upson Hall, llee@cs.cornell.edu.
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Amanda Holland-Minkley, Upson 4116, hollandm@cs.cornell.edu.
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Milo Polte, mp98@cornell.edu.
-
Neeta Rattan, nsr3@cornell.edu.
Time and Location
MWF Upson 205, 9:05-9:55.
Back Course Materials
Copies of handouts, including the September 3 Course Information handout
which contains much administrative information for the course, will be
available in the racks outside Upson 303. Unclaimed homework and exams
for which batch return has been permitted will be available in Upson 303.
Syllabus:
Computation
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Computer problem solving; Deep Blue and computer chess; search techniques;
game-tree search.
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Learning: neural nets and perceptrons; the perceptron learning algorithm;
nearest-neighbor learning.
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Turing machines and the limits of computation
Information
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Information retrieval: Boolean and vector space models; term-weighting.
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The World Wide Web: link structures, search algorithms, and hubs and authorities;
Zipf's law and communities; Erdos-Renyi, preferential attachment, and copying
models.
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Natural language processing: context-free grammars and formal models of
syntax; pushdown automata; computational approaches to discourse analysis;
Zipf's law and probabilistic models of language; Japanese word segmentation;
knowledge-based and statistical machine translation; the Federalist Papers
and statistical authorship attribution; statistical language learning in
infants.
Intelligence
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The Turing Test, the Chinese Room, and the Loebner Prize.
Required Texts
Margaret Boden (1990). The Philosophy of Artificial Intelligence,
Oxford University Press.
David Stork and Arthur C. Clark (1998). Hal's
Legacy; 2001's Computer as Dream and Reality, MIT Press.
Note: the Dewdney book is not required.
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