CS531 Artificial Intelligence

School of Electrical Engineering and Computer Science
Oregon State University
Corvallis, OR 97331-3202

Instructor: Prasad Tadepalli
Office: 3069 Kelley Engineering Center
Instr. Office Hrs: W 11:00-12:00, F 12:00-1:00 PM, KEC 3069
Class Time: MWF 10:00-10:50, Location: Stag 132
E-mail: tadepall at eecs
Class Web page: www.eecs.orst.edu/~tadepall/cs531/09

Text:

Russell and Norvig -- Artificial Intelligence: A Modern Approach 2'nd edition The text is required. We will follow the text fairly closely.

Course Description:

Intelligent agents. Problem-solving as search. Representation, reasoning, and learning with propositional representations. Propositional logic. Reasoning with propositional logic: backward chaining, Davis/Putnam, WalkSAT. Constraint satisfaction methods; Arc-consistency. Belief networks. Inference using variable elimination algorithm. Propositional learning algorithms such as rules, decision trees, naive Bayes, perceptrons, neural networks. Bias-variance trade-off in parameter estimation. EM algorithm for belief networks with hidden variables.

Prerequisite:

I assume graduate standing in Computer Science and strong programming experience in an object-oriented language like C++ or Java.

Your grades are posted here by a secret class number I assigned to you. Let me know if you find any errors.

Schedule:

Midterm: Nov 2, 10 AM, STAG 132 --- 20%
Programming Assignments --- 20%
Homework Assignments --- 20%
1. Home work #1 , Due: 10/7/09
  Answers to chapter 1 questions
2. Home work #2 , Due: 10/14/09
  Answer 3.5
3. Home work #3 , Due: 10/21/09
4. Home work #4 , Due: 10/30/09
5. Home work #5 , Due: 11/11/09
In-class Quizzes --- 10%
Final: Dec, 8'th, tuesday 9:30, STAG 132 --- 30%

Course contents:

What is AI? (Ch 1)
Intelligent Agents (Ch 2)
Problem Solving by Search (Ch 3)
Informed Search (Ch 4)
Constraint Satisfaction (Ch 5)
Adversarial Search (Ch 6)
Propositional Logic (Ch 7)
Representing Uncertainty (Ch 13)
Probabilistic Reasoning (Ch 14)
Learning from Observation (Ch 18)
Statistical Learning (Ch 20)
Review

Students with disabilities:

Students with documented disabilities who may need accommodations, who have any emergency medical information the instructor should know, or who need special arrangements in the event of evacuation, should make an appointment with the instructor as early as possible, no later than the first week of the term. In order to arrange alternative testing the student should make the request at least one week in advance of the test. Students seeking accommodations should be registered with the Office of Services for Students with Disabilities.

Collaborations:

Each student is responsible for his/her own work. I allow collaboration on programming assignments in groups of two. You need to find partners by yourself. You can also do them on your own. Oral discussion of class topics with your peers is encouraged, but collaborations on homeworks and uses of material on the web or elsewhere is strictly prohibited. Please be warned that such transgressions will be taken very seriously and could result in an F (fail) grade for the course. Please refer to the department policy on dishonesty for further details.