COURSES

Goals

The aim of this course is to learn advanced methods, techniques and systems for supporting complex real-life decision-making tasks. Special emphasis is on learning and mastering advanced methods of decision analysis and multicriteria modeling, and their practical applications for solving complex decision problems.

Curriculum

Introduction: decision making and decision support, decision process, components of decision making, taxonomy of decisions, disciplines related to decision making. Decision analysis: modeling methods and techniques of decision analysis, decision making under risk and uncertainty, decision tables, decision trees, influence diagrams, multi-criteria models, selected multi-criteria modeling methods: Kepner-Tregoe, MAUT, AHP, DEX, TOPSIS, PROMETHEE, UTA. Advanced decision modeling methods: integration of decision trees, influence diagrams and multi-criteria models, integration of data mining and decision modeling, integration of qualitative and quantitative modelling, probabilistic and confidence modelling, aggregation functions, decision model revision. Practical training: practical use of selected decision support techniques and tools.