Objectives and competences
Student will:
• in-depth understanding of decision theory, its role and meaning in the process of complex problem solving;
• ability to independently organize and lead complex decision processes;
• Ability to independently develop decision models in the a specific context;
• ability to argument the selected alternative and critically evaluate decision analysis results.
Content (Syllabus outline)
- Cybernetic based decision-making, Sets and measurement
- Human in the decision-making process.
- Decision Models.
- Decision matrics and decision trees.
- Decision making under uncertainty.
- Value of Information.
- Bayesian decision model.
- Basics of Game Theory in decision-making and Decision making under complete uncertainty.
- Judgement under uncertainty and the certainty equivalent.
- Framing of Information and Prospect theory.
- Multiple criteria decision making.
- Group decision-making.
- Contemporary Decision Support Systems (data-driven decision-making, data analytics, data mining, artificial intelligence methods in decision-making).
Learning and teaching methods
• Lectures,
• seminars,
• case studies,
• practical work on the PCs.
Intended learning outcomes - knowledge and understanding
Knowledge and understanding:
After completing the course the students will be able to:
• Identify and formulate the decision problem (alternatives, criteria, and state of the environment).
• Select an appropriate method for the decision-making while taking into account limitations and risks.
• Form the criteria function and to select the solution and critically assess results of decision analysis
• Master the use of group decision making techniques.
• Master the use of decision support software.
Readings
Temeljna literatura:
1. Kljajić Borštnar, M. (2021). Modeliranje odločitvenega znanja : učbenik. Kranj: Fakulteta za organizacijske vede, 2021. 1 spletni vir (1 datoteka PDF (53 str.)). https://estudij.um.si/mod/resource/view.php?id=316738. [COBISS.SI-ID 96346115]
2. Bohanec, M.: ODLOČANJE IN MODELI, DMFA, 2006.
3. V. Omladič:: Matematika in odločanje, Knjižnica Sigma, 2002.
4. Peterson, M.: An Introduction to Decision Theory. Cambridge University Press, 2009.
5. Hansson, S. O.: Decision Theory: A Brief Introduction, 2005, URL: http://people.kth.se/~soh/decisiontheory.pdf , 7.12.2015.
6. Steele, Katie and Stefánsson, H. Orri, "Decision Theory", The Stanford Encyclopedia of Philosophy (Winter 2015 Edition), Edward N. Zalta (ed.): https://plato.stanford.edu/archives/win2015/entries/decision-theory/
7. Clemen, Robert; Reilly, Terence (2014). Making Hard Decisions with DecisionTools: An Introduction to Decision Analysis (3rd ed.). South-Western Cengage Learning.
8. Courtney, J.F. (2001). Decision-making and knowledge management in inquiring or ganizations: Toward a new decision-making paradigm for DSS, Decision Support Systems, 31, pp. 17–38.
Prerequisits
Conditions for taking the exam are: completed assignements of e-study units and seminal work.
Additional information on implementation and assessment Completed Assignements (20 %)
Written exam (60 %)
Seminar work (20 %)
Exam admission requirement:
positive evaluation of a seminar work and its defence (positive is 50% or more)
