Problem solving methods; problem spaces; search techniques; knowledge representation; programming languages for AI; games; predicate logic; knowledge-based systems; machine learning; planning techniques; reactive systems; artifical neural networks; natural language understanding; computer vision; robotics.
Computational systems are very good at repetitive tasks that are completely specified in advance. They do not perform so well at tasks that are poorly specified. The course presents Artificial Intelligence as providing the potential for making computers more useful, motivated in part by biological systems. Engineering applications are used to illustrate the concepts.
Design Technical Elective for CPE; Technical Elective for EE
2574; STAT 4714
ECE 2574 is needed to ensure a modest level of programming ability. STAT 4714 is needed as a background for discussions of inductive inference and machine learning.
Percentage of Course
|What is artificial intelligence?||5%|
|Languages for Artificial Intelligence programming: Lisp, Prolog||10%|
|Problems and Problem Spaces||5%|
|Basic Problem Solving Methods and Heuristic Search||10%|
|Predicate Logic and Theorem Proving||10%|
|Knowledge-based (Expert) Systems||10%|
|Natural Language Understanding||10%|
|Computer Vision and Scene Analysis||5%|
|Planning Methods and Reactive Systems||10%|