Fall 1999

308-424A

Topics in Artificial Intelligence

Last update: Fall 1999.

Recent news, updates and current information, including assignments, is lower on the page, under "Hot news".

This page: Instructor | TAs | News | Description | Syllabus | Marking | Hot news
Other pages: Resources | Lectures

General Information

• Location: Burnside MC13
• Times: Tuesdays and Thursdays, 2:30-4:00pm

Instructor:

Professor G. Dudek,
School of Computer Science.

Email: dudek@cs.mcgill.ca (SEE NOTE ON EMAIL, BELOW)
Office hours: Tues. & Thurs. 1-1:30 and 4-4:30 in class. Other times by appointment.
Office: McConnell 419
Telephone: 398-4325.

Important Information:

IMPORTANT: For most course-related email (that could be addressed by a TA), you should use the class email account, not that of specific TA's or the Professor.

Prerequisites:	Required: 308-203 or 308-250. 308-330 is recommended. A knowledge of programming under UNIX is assumed.
Class email account:	cs424@cs.mcgill.ca
Class web page:	<http://www.cim.mcgill.ca/~dudek/424/ai.html>
Frequently asked questions and assignment tips:	~cs424/FAQ.html

Textbook:

Stuart Russell and Peter Norvig, "Artificial Intelligence: A Modern Approach", Prentice Hall, 1995. 932 pages, $97.95.

Secondary references:

"Artificial Intelligence: Theory and Practice" by: Thomas Dean, James Allen, Yiannis Aloimonos 563 pages

Bonnie Lynn Webber and Nils J. Nilsson, "Readings in Artificial Intelligence", Morgan Kaufmann, San Mateo, CA, 1981.

 

Handouts: Some of the handouts may be (will-be) available online. So far, it's only the administrative handout, which essentially the same as this web page.

Teaching Assistants :

• Yiannis Rekleitis (yiannis@cs.mcgill.ca) (SEE NOTE ON EMAIL, ABOVE)
• Eric Bourque (ericb@cim.mcgill.ca) (SEE NOTE ON EMAIL, ABOVE)

TA's office hours:

1:30-2:30 T,Th MC403.

Hot news

• The tournament : partial results are visible at http://www.cim.mcgill.ca/~dudek/424/%25players.html
• The exam took place Dec. 14th and was, reportedly, not that easy althoughA that is based only on rumor.
• Assignment 4 can be handed in 5 days late without penatly.
• Assignment 4: 424-99-asst4.html
• Project server interface in the C language is here: http://www.cim.mcgill.ca/~ericb/424/libdrax/docs.html. At present, there is no java interface. We will attempt to provide one, but it will take two more weeks. Don't wait for it!
• The sever can be found at http://www.cim.mcgill.ca/~ericb/424/drax/docs.html
• The final project is now pending. If you plan to submit one, you must sign up using the web page at http://www.cim.mcgill.ca/~ericb/424/signup.html.
• Assignment 3 is due November 2nd.
• The special seminar by Nicholas Roy is Monday Oct. 25th at 11am in MC 437.
• The mid-term test was in class on October 7th. It covered all material covered in class as well as assigned reading up to and including the lecture of Sept. 30.
• Assignment 2 is due Oct 14th.
• Assignment 1 was specified and is due Sept. 28th.
• Sept 14: readings were assigned in class. Read chapters 6 & 7. Do some problems from the back of these chapters. Try finding and running a prolog interpreter.
• See the resources page for supplementary materials.
• Some notes will be provided using PDF-format files. The reader for PDF files is available free from Adobe for UNIX, Macs, and other platforms . PDF files can also be viewed using ghostscript.
• The textbook is available in the bookstore.
• The administrative handout (like this initial version of this page) is available by clicking here.

Course Description

This class focusses on Selected Topics in Artificial Intelligence. We will study modern techniques for computers to make good (in some cases optimal) decisions that are applicable throughout an enormous range of industrial, civil, medical, financial, robotic and information systems. We will focus on core AI algorithms. Near the end of the course we will spend several lectures learning about and discussing some important current application areas of AI.

Evaluation

Evaluation will be based on:

• Four assignments together worth 28% of the final mark
• A final project worth 26%
• A midterm worth 7%
• A final exam worth 39%

Syllabus

The schedule is VERY TENTATIVE.

Fundamentals

• Overview of AI (week 1; chapter 1)
• Knowledge representation and inference (weeks 2 &4; chapter 3 &6)
• Search (weeks 3 & 5; chapter 4)

Learning and Reasoning

• Symbolic learning (week 6; chapter 5, first half)
• Learning in neural networks (week 7; chapter 5, second half)
• Either (week 8)
  • Genetic Algorithms, or
  • Probabilistic and fuzzy reasoning (chapter 8)

Perception and Action

• Vision (week 9 & 10; chapter 9)
• Action: planning and robotics (week 11; chapter 7)
• Natural language (week 12; chapter 10)

Review, project discussions

• Discussions (week 13)

Tentative Lecture Plan

Lecture notes are in PDF format.

On PDF format: Some notes will be provided using PDF-format files. The reader for PDF files is available free from Adobe for UNIX, Macs, and Windows. PDF files can also be viewed using ghostscript.

The lecture plan and some notes can be found on a separate page.

Rules: The fine print

1. Homework is to be submitted both in electronic form, using the handin program (on UNIX) and, as necessary, in paper form dropped off in the 424 slot of the assignment drop-off box near the 1st floor labs.
2. Assignments that are under 24 hours late get no penalty. Assignments that are over 1 day (24 hours) late but under 2 days (48 hours) late are penalized 20 per cent. Assignments will not be accepted more than 2 days late.
3. Re. late assignments: Any fraction of a day counts as one day; Saturday+Sunday count as one day.
4. Class attendance will not be recorded but the most important stuff will happen in class.