When: Mondays and Wednesdays, 1:00-2:30pm.
What: One of the primary goals of AI is the design, control
and analysis of agents or systems that behave appropriately in various
circumstances. Such intelligent agents require the ability to decide
how to act as circumstances vary. In turn, good decision making
requires that the agent have knowledge or beliefs about its
environment and its dynamics, about its own abilities to observe and
change the environment, and about its own goals and preferences. In this course
we will examine some of the techniques for modeling decision problems
of various types and the computational methods used to solve them. We
will focus mainly on probabilistic models of reasoning, and on
sequential decision making.
The course is intended for advanced undergraduate students and for graduate students, and will provide an introduction to the on-going research in the field of reasoning under uncertainty, which has been very active during the last decade.
The course will cover both the theoretical basis of decision making under uncertainty, and the practical applications of these algorithms. We will cover the following topics:
Office: McConnell 326
IMPORTANT: E-mail is the quickest way to reach me and get your questions answered.
Office Hours: Thursdays, 2:00-3:00, McConnell 231