CS 541 Artificial Intelligence

Credit Hours: 3
Course Coordinator: Melanie Mitchell
Course Description: An introduction to the basic concepts and techniques of artificial intelligence.
Prerequisites: CS 202, 311, or equivalent
Goals:

This course will provide students with an overview of the major topics and techniques of current-day artificial intelligence. Upon the successful completion of this course students will be able to:

  1. Describe several real-world applications of AI.
  2. Describe and implement AI search techniques for heuristic problem-solving and game playing, and describe their strengths and limitations.
  3. Describe and implement various AI knowledge-representation techniques.
  4. Design software agents that use Bayesian techniques to learn and reason under uncertainty.
  5. Design software agents that use reinforcement learning techniques.
  6. Design simple genetic algorithms.
  7. Describe some of the major approaches to current-day research on natural-language processing, computer vision, analogy-making, and robotics.
  8. Summarize major philosophical and ethical questions regarding AI.
Example Textbooks: None. Required readings will be posted on the class web site.
References: None
Major Topics: Application areas of AI, problem-solving and game-playing as search, knowledge representation, biologically inspired AI, learning and reasoning under uncertainty, natural-language processing, vision, analogy-making, robotics, philosophy of AI.
Laboratory Exercises: