CS 642: Techniques in Artificial Intelligence:
LOGIC AND ARTIFICIAL INTELLIGENCE
Fall 1985 William J. Rapaport
MWF 2-2:50 Bell 214
Cooke 127A 636-3193
Office Hours: tba & by appointment
TEXTS:
Required:
(1) James D. McCawley, Everything that Linguists Have Always
Wanted to Know about Logic but Were Afraid to Ask (Chicago:
University of Chicago Press, 1981)
(2) Bonnie Lynn Webber and Nils J. Nilsson (eds.), Readings in
Artificial Intelligence (Palo Alto: Tioga, 1981)
Recommended:
(1) Morton L. Schagrin, William J. Rapaport, and Randall R.
Dipert, Logic: A Computer Approach (New York: McGraw-Hill,
1985)
(2) C-L. Chang and R. C-T. Lee, Symbolic Logic and Mechanical
Theorem Proving (Orlando, FL: Academic Press, 1973)
(3) Larry Wos, Ross Overbeek, Ewing Lusk, and Jim Boyle,
Automated Reasoning (Englewood Cliffs, NJ: Prentice-Hall,
1984)
In addition, there may be reading assignments from journals and
conference proceedings.
TOPICS: This course will be an introduction for Computer Science
students to various systems of logic and an investigation of the
applications of logic to such diverse branches of AI as mechani-
cal theorem-proving and knowledge representation. Topics to be
covered will include some or all of the following (as time per-
mits):
propositional logic circumscription
predicate logic modal logics, including:
Herbrand's Theorem epistemic logic
resolution deontic logic
unification fuzzy logic
deductive question-answering many-valued logic
and erotetic logic limitations on reasoning and
relevance logic the "neat/scruffy" debate
MECHANICS OF THE COURSE: You will be expected to attend all
classes, and to complete all readings and assignments on time.
There will be regular homework assignments and a term paper or
programming project.
The course is open to interested graduate students in Computer
Science, Philosophy, Linguistics, Mathematics, etc.
Pre-requisite:
Graduate standing in Computer Science, or permission of
instructor, or some prior knowledge of AI or logic. No pro-
gramming experience is necessary.