Portale di Ateneo - En.Unibs.it

1. Introduction to decision problems.

2. Decision criteria: max-min, max-max, realism, max-min regret, equiprobability, the expected value.

3. Uncertainty and probability: encoding the probabilities; probability trees and their analysis.

4. Decisions with uncertainty: good decisions and good results; rules for constructing influence diagrams; construction of the decision tree; the decision tree analysis; the value of perfect information; the value of perfect control.

5. Probabilistic dependence: dependence and independence; conditional probabilities and dependent outcomes; the tree of the nature and Bayes' rule; the value of imperfect information.

6. Risk aversion: describing risk aversion and risk attitude; utility functions and their use; exponential function and risk tolerance.

7. Multi-objective decisions: basic concepts; the additive utility function: normalizing and weighting the objectives.

8. Use of spreadsheets for the analysis of cases.