After taking this course, you should be able to:

• Define a new problem to be solved in terms of searching for a solution. Understand several search algorithms, and which ones are most likely to be useful in which problem-solving environments.
• Represent symbolic knowledge about an agent's environment. Understand several logical inference methods for reasoning about this knowledge in order to decide what to do.
• Put these techniques together to build computer programs that plan ---search for appropriate sequences of actions--- when solving problems in an environment.
• Understand techniques to represent and reason about uncertain knowledge, including uncertainty about the outcomes of agent actions, or the causes of an observable fact.
• Write a computer program that learns, i.e., modifies itself (by gathering new knowledge) so that it succeeds at solving a problem at which it initially failed.

Parts of the course are subject to change to meet your needs as students.