CS 416

Introduction to Artificial Intelligence

Spring 2008
(1019V)


Time: Tuesday/Thursday 3:30 - 4:45
Place: Olsson 120
Instructor:
W.N. Martin
Email: martin@virginia.edu
Office: Olsson 213
Office Hours: Tues/Thurs 5-6:30pm
Office Phone: 982-2202

Assistant:
Ben Hocking
Email: hocking@virginia.edu
Office: Olsson 001
Office Hours: Wednesday 5-7pm
Web Page http://www.cs.virginia.edu/~cs416/
 
Prerequisites: CS 201, CS 202, CS 216.  Calculus required.  Basic linear algebra and statistics is recommended, but will be reviewed in class. As this course is intended for upper-class computer science majors, the CS 216 prerequisite represents a minimal amount of programming skills.  The programming will require significant programming efforts.
 
Textbook: Artificial Intelligence, Theory and Practice
by Dean, Allen and Aloimonos
 
Topics: Search: informed, uniformed, adversarial
Optimization: Simulated annealing, conjugate gradient, genetic algorithms
Propositional logic and theorem proving
Machine learning: Bayesian, hidden Markov models, neural networks
Natural Language Processing
Computer Vision





Grading


Programming
Assignments:
There will several programming assignments in this course.  Source code documentation and organization should make your programs easy to read and convey your understanding of the implemented functions.  Documentation and programming style will part of the evaluation.  More detailed instructions regarding required documentation will be provided with each assignment.
 
Homeworks: There will be both in-class and out-of-class assignments that will be evaluated for this part of your grade.
In-class Exams: Exam 1: Thursday, February 28th
Exam 2: Tuesday, April 22nd
Final Exam: Tuesday, May 6th
9am-12noon, Olsson 120
Class Participation: Both joining class discussions and asking/answering questions are important for this evaluation.
Distribution
Programs: 30%
Homework: 20%
Exam 1: 13%
Exam 2: 13%
Final Exam: 19%
Class Participation: 5%
Total: 100%

Late assignments will always be accepted, however, at 10% per day penalty will be applied for every calendar day after the original due date.
For exams, no "after the fact" arrangements will be made for a missed exam without a written note from Dean Marshall's office.


Honor Code: The honor code applies to all work turned in for this course. In particular, all code and documentation should be entirely your own work. You may consult with other students about high-level design strategies related to programming assignments, but you many not copy code or use the structure or organization of another student's program. Said another way, you may talk with one another about your programs, but you cannot ever look at another student's code nor let another student look at your own code. Each assignment will include a specific Honor Code Guideline referring to the use of online materials.