CS480: Artificial Intelligence - Fall 2011

Course Description

Introduction to computational methods for intelligent control of autonomous agents, and the use of programming paradigms that support development of flexible and reactive systems. These include heuristic search, knowledge representation, constraint satisfaction, probabilistic reasoning, decision-theoretic control, and sensor interpretation. Particular focus will be places on real-world application of the material. Prerequisites: CS 331, and CS 401, or CS 403.

Course Topics

The following is a tentative and partial list of topics that will be covered in the class:

Course Information

Time and Location: Mon - Wed 1:50 - 3:05pm in Stuart 238
Mustafa Bilgic
Office: Stuart 228C
Email: mbilgic AT iit.edu
Office Hours: Mon - Wed 11am - 12pm (Other times by appointment)


CS 331, and CS 401, or CS 403.

Course Format and Grading

In my couse, the slides often serve only as a guide; I use the white board heavily. 

The evaluation will consit of written assignments (~six), programming assignments (~three), a midterm, and a final. The point breakdown is:

Late submission policy: You have seven free late days without penalty. You can use those days in any way you like for the written and/or programming assignments; you can use all of them for a single assignment or use them sparingly. However, once you run out of free days, late submissions will not be accepted. Absolutely positively no exceptions. So, use them wisely.
Collaboration policy: You can discuss the written assignments with your friends; however, everyone has to write their own solutions in their own words.
Code of academic honesty: Please read the procedures on academic honesty here. If you violate the academic honesty (such as unauthorized collaboration, cheating, etc.), then depending on the severity of the violation, it can result in i) getting zero points on the respective assignment, ii) expulsion from the course, iii) suspension of your enrollment at the university, iv) expulsion from the university.

Course Material

There is a required text book for this course:

Artificial Intelligence: A Modern Approach, 3rd edition, by Stuart Russell and Peter Norvig

There will be additional reading materials (mostly available on the web).

Tentative Schedule

Date Topic Required
Aug 22
Introduction and Course Overview
ch. 1
Aug 24
Intelligent Agents & Problem Solving
ch. 2
Aug 29
ch. 3
Aug 31
Sep 5
Sep 7
Game Playing
ch. 5
Sep 12
Game Playing
Sep 14
Constraint Satisfaction Problems (CSPs)
ch. 6
Sep 19
CSPs and Constraint Propagation
Sep 21
KR & Logical Agents
ch. 7
Sep 26
Resolution & Theorem Proving
Sep 28
First Order Logic (FOL)
ch. 8
Oct 3
FOL & Theorem Proving
ch. 9
Oct 5
Oct 12
Oct 17
ch. 11
Oct 19
ch. 12
Oct 24
ch. 13
Oct 26
Probabilistic Reasoning
ch. 14
Oct 31
Probabilistic Reasoning
Nov 2
Probabilistic Reasoning
ch. 15
Nov 7
Decision Making Under Uncertainty
ch. 16
Nov 9
Decision Making Under Uncertainty
Nov 14
Decision Making Under Uncertainty
ch. 17
Nov 16
ch. 18
Nov 21
ch. 20
Nov 23
Nov 28
Reinforcement Learning
ch. 21
Nov 30