Decisions under uncertainty

• Analyse a decision problem to point out uncertainties and understand what effect these uncertainties have on the decision-making
• Describe the procedure in each of the presented methods for decision making based on uncertain information
• Design and utilise computational tools to employ the presented methods
• Design computational experiments for validating modelling choices for the decision making problem and relevant uncertainties
• Apply the presented methods on a specific decision problem characterised by uncertain information
• Explain how the different methods can complement one another to gain further insight
• Contrast alternative methods for representing uncertainty in decision making from a quantitative standpoint
• Deduce recommendation based on the application of the presented methods for decision problems characterised by uncertain information

Students will be introduced to different quantitative methods for decision problems characterised by uncertain information. These methods include decision analysis, Markov chains, simulation, and stochastic programming.

02002, Computer Programming (02002)

Lectures and exercises