GS/COSC 6390A Knowledge Representation
Fall 2006

Department of Computer Science and Engineering,
York University

An In-Depth Survey of Knowledge Representation and Reasoning

The course examines some of the techniques used to represent knowledge in artificial intelligence, and the associated methods of automated reasoning. The emphasis will be on the compromises involved in providing a useful but tractable representation and reasoning service to a knowledge-based system.

What's new:

Instructor

Prof. Yves Lespérance
Office: CSE-3052A
Tel: 736-2100 ext. 70146
Email: lesperan "at" cse.yorku.ca

Lectures

Wednesday from 19:00 to 22:00 in CB-120.

Instructor Office Hours

Wednesday 17:00 - 18:00 and Friday 13:30 - 14:30,
or by appointment.

Textbook

Ronald J. Brachman and Hector J. Levesque, Knowledge Representation and Reasoning, Elsevier/Morgan Kaufmann 2004, ISBN 1-55860-932-6

Recommended but not required; lecture notes (slides) will be distributed, which are often sufficient; textbook is on reserve at Steacie Library.

Prerequisites

Knowledge of first-order logic and Prolog.

Tentative Evaluation

Assignements (4 @ 12.5% each)      50%
In-class tests (2 @ 25% each)      50%
Total 100%

Tentative Schedule

Additional References

A good Prolog text:

Clocksin, W.F. and Mellish, C.S., Programming in Prolog, (5th edition), Springer Verlag, New York, 2004.

On knowledge representation:

Baral, C. Knowledge representation, reasoning, and declarative problem solving. Cambridge University Press, Cambridge/New York, 2003.

Genesereth, M.R. and Nilsson, N.J. Logical foundations of artificial intelligence. Morgan Kaufmann, Los Altos, CA, 1987.

On reasoning about action:

Reiter, R., Knowledge in Action: Logical Foundations for Specifying and Implementing Dynamical Systems, MIT Press, 2001. York Library eCopy, Book home page.

On AI:

Russell, S.J. and Norvig, P., Artificial Intelligence: A Modern Approach, Prentice Hall, 1995.

Running SWI-Prolog on the York CSE Research System or Prism

Getting Prolog

About Prolog