Version of 7 January 2007

Course description, from the catalogue:

CSG120 Foundations of Artificial Intelligence
This course introduces the fundamental problems, theories and algorithms of the Artificial Intelligence field. Topics covered include: heuristic search and game trees; knowledge representation using predicate calculus; automated deduction and its applications; problem solving and planning; introduction to machine learning. Required coursework includes the creation of working programs that solve problems, reason logically, and/or improve their own performance using techniques presented in the course. Prerequsite: Java programming (Lisp optional).

Course Key Number:

40274

Institution:

Northeastern University, and the College of Computer and Information Sciences, Boston, MA.

Instructor:

Professor Robert P. Futrelle   Email me at: futrelle@ccs.neu.edu,
but note the important emailing instructions at the end of this page.

Futrelle's Office:

450 West Village H (WVH). Also check my lab 460 WVH.

Hardcopy mailbox:

202 West Village H (WVH)

Telephone:

Futrelle's office: 617-373-4239, Lab: 617-373-4607

Textbook:

Artificial intelligence : A Modern Approach by Stuart J. Russell and Peter Norvig Prentice Hall/Pearson Education, 2003. 2nd ed. 1080 pgs, ISBN: 0137903952. (which I will refer to as "AIMA") See the AIMA homepage. Do not get the earlier, first edition; it is inappropriate for this course.

Personal Help:

Regular office/advising hours: Mondays, 1-2pm; Wednesdays 4:45-5:45pm.
IM hours below.
If you need help at any other time, find Prof. Futrelle or call or send email, or ask in class to set up an appointment.

Instant Messaging office hours:

Google Chat: futrelle.teach@gmail.com Monday and Wednesday evenings 8-10pm.
Other IM providers may be added, but I'll limit IM to Google Chat initially. If you need a Google account, I'd be happy to give you one. Google talk is available for voice contacts, Windows only (it runs fine for me in XP SP2 under Parallels on my MacBook Pro).

On-line help:

There is a ton of information about Artificial Intelligence on the web. The best sources are probably the links on the homepages for the textbook: AIMA homepage, as well as a page of links created for me recently by a student, which I'll be revising.

Professor Futrelle's teaching blog:

Read the blog here.

Classes:

Thursdays 6pm - 9pm in 110 Kariotis

Projects:

Information will be available on the Projects page.

Course homepage:

http://www.ccs.neu.edu/home/futrelle/teaching/csg120sp2007/index.html

Grading:

Points of credit out of 100 points for the course:

• Quiz #1 on the Overview (closed book, notes) 4 points
• Quiz #2 on Bayes and Learning (open book, notes) 4 points
• Midterm Exam (closed/open book) 20 points
• Each of the five assignments 4 points 20 points (total)
• Project initial report 5 points
• Project interim report 7 points
• Project final submission (includes class presentation) 18 points
• Final Exam (take-home) 22 points

The course mailing list and archives:

The subject line in all non-mailing list mail to me regarding the course must begin with csg120sp07, or else it will be returned.
All students in the course must sign up for the mailing list in order to receive important notices. Sign up right away at https://lists.ccs.neu.edu/bin/listinfo/csg120-sp07-rpf. You can only post mail to the list using the email address(s) you're signed up with, though you may sign up with more than one address - and receive mail sent to one, the other, or both. Group membership is private. All mail to the list is publicly archived and available here: https://lists.ccs.neu.edu/pipermail/csg120-sp07-rpf/. Post away -- your questions and information may well be of interest to other students in the class. Post mail to the list from your registered email address(s) to this address: csg120-sp07-rpf@lists.ccs.neu.edu (Mail to the list will automatically be prefaced with the course label for you.)

Go to CSG120 home page. or RPF's Teaching Gateway or homepage