3 credits | Prepared by Ronnie W. Smith, August 2018 |
P: CSCI 2540 or CSCI 3200 or consent of instructor. Fundamental problems and techniques of artificial intelligence. Heuristic search. Concepts of expert systems.
This course concentrates on the fundamental problems and solution techniques used in problems associated with artificial intelligence. Fundamentals of knowledge representation and search are presented along with a discussion of topic areas such as machine learning, planning, natural language processing, automated reasoning, and reasoning under uncertainty.
Artificial Intelligence: Structures and Strategies for Complex Problem Solving, George F. Luger. Addison Wesley, 2009, 6th.ed.
Grading will be based on midterm exam, final exam, homework assignments, and a comprehensive project. The midterm exam will count 15%, the final exam 25%, the homework assignments 40% and the project 20%.
Grade | Meaning |
---|---|
A | Achievement substantially exceeds basic course expectations |
A− | |
B+ | |
B | Achievement exceeds basic course expectations |
B− | |
B+ | |
C | Achievement adequately meets basic course expectations |
C− | |
D+ | |
D | Achievement falls below basic course expectations |
D− | |
F | Failure – achievement does not justify credit for course |