The course is cross-listed in Intelligent Systems Program as ISSP 2240. It is also an honors course, i.e., open for students in University of Pittsburgh's Honors College.
"The average man's judgment is so poor, he runs a risk every time he uses it." --- Edgar W. Howe
Most real world problems involve uncertain information. Although uncertainty can be often reduced, it can be seldom eliminated and whether we are dealing with scientific, engineering, or personal problems, we are forced to make decisions that are based on incomplete knowledge. Even a deliberation of whether more information should be collected before making an actual decision is itself a decision under uncertainty. Decision making under uncertainty has been addressed in mathematics by probability theory and expected utility theory. These two together are known as decision theory. The discipline that focuses on applying decision theory in practice is known as decision analysis. Decision analysis offers a set of structured procedures that assist decision-makers in
This course provides an introductory treatment of decision analysis, along with elements of human cognition under uncertainty. The intended participants are students who want to learn more about decision making under uncertainty and tools that can be used to support it. Knowledge of these tools may prove useful in your personal decision making and in decisions that you will be making during your professional career. Should you choose to become a professional supporting decisions of others (and this is a good way to make a living), this course will lay foundations for your future studies. Most of all, and this is the reason why this course is in the information science foundations area and is cross-listed in the Intelligent Systems Program, this course should give you solid foundations for applying the ideas of decision analysis in intelligent information systems and decision support systems.
As you might have already experienced by now, being an engineer or a scientist requires intelligence, independent, creative thinking, and most of all commitment to hard working. This course reinforces this. The material is not really difficult, but you will have to invest quality time in order to master it. There will be a term project that will normally involve applying the methods learned in the course to model a real (or realistic) decision and build a decision support system to support it. The workload in this class will be heavy, but I believe that you will find it interesting and important. I require your commitment, doing the readings, coming to classes, and being their active participant. In return, I promise that you will have fun and you will learn useful skills.
Syllabus (Spring 2014, PDF)
Marek Druzdzel's teaching page
Marek Druzdzel's home page