This PhD-level course on decision theory focuses on advanced theories of individual and group decision making under risk and uncertainty. The course briefly explores utility theory under certainty and the notion of preferences and their representation, then progresses to the classic theories of decision under risk and uncertainty. Application Decision support Systems, Expert Systems, Knowledge-based systems in process of managerial decision making.

Upon successful completion of this course, students should be able to: - Formulate and design a model the complex problem of decision-making, - Decompose a complex problem of decision-making, - Identify a method to solving each decomposed part of a complex decision-making problem, - Solve the complex problem of decision-making, independently or with the assistance of a adequate software tool for decision-making.

The course consists of three major sections: 1) modeling decisions, where the emphasis is on structuring decision problems using techniques such as influence diagrams and decision trees; 2) modeling uncertainty, which covers subjective probability assessment, the use of classical probability models, Bayesian analysis, and value of information; and 3) modeling preferences, which introduces the concepts of risk preference, expected utility, and multi-attribute value and utility models.

Design knowledge-based system for problem defined in doctoral thesis methodology.

Enrolled 1st semester of doctoral studies.

On-line free academic access to electronic databases: ebesco, science-direct, emerald, etc. Computer classroom. Real practical example in pilot factory - access to real data and database in for purpose of solving real practical complex managerial problems.

Total assigned hours: 65

New material: 40
Elaboration and examples (recapitulation): 10

Auditory exercises: 0
Laboratory exercises: 0
Calculation tasks: 0
Seminar paper: 0
Project: 0
Consultations: 0
Discussion/workshop: 0
Research study work: 0

Review and grading of calculation tasks: 0
Review and grading of lab reports: 0
Review and grading of seminar papers: 10
Review and grading of the project: 0
Test: 0
Test: 0
Final exam: 5

Activity during lectures: 10
Test/test: 0
Laboratory practice: 0
Calculation tasks: 0
Seminar paper: 40
Project: 0
Final exam: 50
Requirement for taking the exam (required number of points): 30

Maynard, H.B, , 1971, Industrial Engineering Hadbook, McGraw Hill, New York, third edition, pp.1532; Bazerman, M.H., Moore, D.A, 2008, Judgment in managerial decision making, 7th ed., John Wiley and Sons, pp.230.; Blake, C., 2008, The Art of Decisions: How to Manage in an Uncertain World, Prentice Hall, pp.232; Adair, J.E., 2009 Effective Decision Making: The Essential Guide to Thinking to Management Success, Pac Macmillan, pp.192.; Zeleny, M., 1982, Multiple criteria decision making, McGraw-Hill, New York.