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.