CS 2710 / ISSP 2610, Foundations of Artificial
Intelligence, Fall 2013
When and Where: Fall 2013 M W 11:30am-12:45pm, 5313 Sennott Square
Professor: Dr. Jan Wiebe, Sennott Square Rm 5409,
412-624-9590, janycewiebe - at - gmail,
Professor Office Hours: T 12:30-1:30pm; Thurs 2-3pm; and by appointment
Teaching Assistant (TA): CharmGil Hong, Sennott Square Rm
charmgil at cs dot pitt dot edu
TA Office Hours:
Wed 1-2pm; Thurs 10am-12pm; and by appointment
Knowledge of Computer Science
through CS1501 and CS1502.
Textbook: Artificial Intelligence: a modern approach
(third edition), S. Russell and P. Norvig, Prentice Hall. Be sure to
get the third edition (the one with the blue cover).
Assignments will be a mixture of programming and written
assignments. Some will involve extending code given to you. That
code will be in Python. If you have never used Python, consult the Python
website; a tutorial
Due dates are strict. Extensions will be granted
only in the case of (documented) extreme circumstances.
Exams will be closed book/closed notes/closed electronics.
The final will cover the entire course.
There is a schedule on
the course web page.
The schedule includes topics, lecture notes, due dates,
assignments, specific reading assignments,
and exam dates.
It will be updated as the course
Assignments must be your own individual work, unless explicitly stated
You must do the work without undue help from other people, and you
not present material from resources such as the Web, books, papers,
and other people as your own.
You may talk to each other about concepts and techniques, but you must
not discuss specific solutions or approaches to solutions.
Academic Integrity Code for the Deitrich School of Arts &
Students With Disabilities:
If you have a disability for which you are or may be requesting an
accommodation, you are encouraged to contact both your instructor and
Disability Resources and Services, 216 William Pitt Union, (412)
648-7890/(412) 383-7355 (TTY), as early as possible in the term. DRS
will verify your disability and determine reasonable accomodations for
Planned Course Content:
Part 0 (1 lecture): Introduction.
[Chapters 1 and 2]
Part I (approximately 7 lectures):
Heuristic Search; Constraint Satisfaction
Adversarial Search. [Chapters 3,4,5,6]
Part II (approximately 6 lectures): Knowledge Representation, Reasoning, Logic
Part III (approximately 4 lectures): Planning [Chapter 10]
Part IV (approximately 8 lectures): Reasoning under Uncertainty; Learning
Acknowledgements: lectures slides
include material from lecture notes by Yu Cao
Cardie, Hal Daume, Charles Elkan, Reva Freedman, Shaun Gause, Reijer Grimbergen, Milos Hauskrecht,
Peter Norvig, Ellen Riloff, Stuart Russell, Ellen Walker.