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The course aims to teach the basic principles and the methods in decision analysis and risk modeling. The goal is to teach modeling decision problems under uncertainty using influence diagrams, decision trees and Monte Carlo simulation, and model risk attitudes of decision makers based on concepts from utility theory.
Modeling of the decision problem: Structuring decisions, influence diagrams, decision trees, risk profiles, sensitivity analysis. Modeling uncertainty: Probability concepts, value of information, Monte Carlo simulation. Modeling preferences: Risk, utility theory, prospect theory.
Having successfully completed this course, students will be able to:
1. Identify elements of decision making, structure and model complex decision problems. (B1,e)
2. Apply appropriate techniques and methods to solve decision analysis problems (B3,k)
3. Assess the value of information (B6,k)
4. Model risk attitudes of decision makers. (B5, k)