About the Course

This course will go in depth in a small number of advanced topics in Artificial Intelligence beyond those covered in CS580. These topics will extend existing knowledge about search, machine learning, reasoning, and situated action. Some topics are required; others may be negotiated with the class. Topics will include at a minimum planning, probabilistic reasoning, and (depending on the background of the class) reinforcement learning and evolutionary computation. Additional topics may include knowledge-based learning, natural language processing, vision, robotics, and advanced machine learning techniques.

Any programming assignements, other than the final project, will be done in Common Lisp, the traditional exploratory programming language of AI. Based on experience in CS580, we assume students will be reasonably well versed in Lisp: however, some advanced topics may be covered (such as CLOS and macros).

Course Information

Textbooks

	The required text is Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig, ISBN: 0131038052.
	As we will be coding in Lisp, I very strongly recommend that you also obtain a text on basic Common Lisp. One good choice is ANSI Common Lisp by Paul Graham, ISBN: 0133708756.

Grading Policies

Homework	25%
Project	25%
Midterms	25% Each

There will be no make-up tests for missed examinations. Late homework will be accepted but at a loss of 20% per day (homework later than 4 days). Late final projects must be negotiated with the instructor.

Cheating. This past semester we had seven incidents of plagarism in CS580. All seven incidents went to the honor court and received, at a minimum, a full grade drop (A->B, B->C, C->F). Moral of the story: this is not the course in which to press your luck.