Course Description: This CS494/594 course on Artificial Ingelligence (AI) covers the breadth of the field of AI, including topics such as problem-solving, search, logic, planning, reasoning, natural language, and perception. We define AI as the study of intelligent agents that receive percepts from the environment and perform actions. We will cover different ways to represent the mapping of percept sequences to actions, such as production systems, reactive agents, real-time conditional planners, and decision-theoretic systems. Our primary aim is to convey the ideas that have emerged over the past fifty years of AI research. Evaluation will be through homeworks, projects, and quizzes. (Some homeworks/projects may involve programming.)

[This course avoids overlap with COSC425/528 (machine learning).]

Prerequisites: Familiarity with basic concepts of computer science (algorithms, data structures, and complexity), and mathematical maturity commensurate with CS312 or equivalent. A foundational understanding of probability (ECE 313) is also needed.

Instructor: Prof. Lynne E. Parker

• Office: Min Kao 617
• Email: leparker at utk dot edu
• Office Hours: Tues/Thurs before and after class (i.e., 10:30-11:00AM, and 12:30-1:00PM), or send email for appointment

TA: Hao Zhang

• Office: Min Kao 620
• Email: haozhang at utk dot edu
• Office Hours: Mon/Wed, 10AM-11AM

• Artificial Intelligence: A Modern Approach, Third Edition, by Russell and Norvig, Prentice Hall, 2010.