CPSC 533: Artificial Intelligence -
| Apr 23:
|| The results of Final and whole course can be
| Apr 16:
|| The Final will be on Wednesday, April 23, from
8am to 10am in SB 144. As usual, there will be lists in the
room that tell you your seat. Do not forget to bring a pen!
I have prepared a list with
questions that you should use to prepare yourself for the Final.
| Apr 5:
|| All teams can now make appointments with me for
their demos. Just send me an email, as explained in the
lecture. The times I am available are as follows:
Wednesday, Apr 9: 13:00-14:00, 14:00-15:00,
Thursday, Apr 10: 11:00-12:00, 16:00-17:00
Friday, Apr 11: 12:00-13:00, 13:00-14:00
14:00-15:00, 15:00-16:00, 16:00-17:00
| Apr 3:
|| As challenge, here is a file containing the slightly modified
TA scheduling problem instance of the Computer Science
Department last fall. I expect each team to submit the
best solution their system found to it (full schedule
with Eval-value of it, assuming weights of 1 for all
soft constraints) together with their source code and
| Mar 18:
|| Students interested in checking their Midterm
can come to the AI lab on Thursday, March 20, 15:30 (until
16:30). Seamus and I will be there to hand out the exams
and answer questions about the exam.
| Mar 12:
|| The results of the Midterm are
| Mar 6:
|| The Midterm will take place on March 11, during
the time of the lecture in ENA 103. I have put together a
of questions that you can use for your preparation for
| Mar 5:
link leads to a description of the input format that
your assignment systems will have to work with. If you have
additional questions, please email me or ask in class.
| Jan 29:
|| Please note the room change for the course!
Starting Jan 30, the lectures will be in SA 104!
| Jan 1, 2003:
|| Site made available to public.
| Dec 12:
|| Course web site started.
Description of the course
According to Calendar:
An examination of the objectives, key techniques and achievements of
work on Artificial Intelligence in Computer Science.
According to me:
On overview on the different fields of AI and its history, an
introduction to knowledge representation and knowledge processing,
especially search as the key problem solving technique and the
different search paradigms, and an overview (with some case studies)
of the areas planing, learning and cooperation (this only if time
Note that a basic understanding in logic is definitely required for
this course. Although we will introduce the basic concepts of how to
process and solve problems described in logic in this course, knowing
what logical formulas, propositions and calculi are and how a problem
can be represented as a set of formulas is a must!
- Computer Science 313,
331 and Philosophy 279 or 377
The main goals of the labs will be to help you in more deeply
understanding the concepts presented in the lectures and with your
|| to an explanation of the assessment of the students
taking the course.
Last Change: 23/4/2003