The purpose of this document is to provide students who participate in the course ‘Intelligent Decision Support Systems (IDSS)’ a guideline about the course contents, lecturing form, literature, examination, and relation to other courses or knowledge.
Goal of the course
This course is to give students knowledge in the area of IDSS, in relation to decision theory and design and implementation of IDSS.
There are two basic topics through the course, one is decision theory and the another is methodology for design of IDSS.
In the topic of decision theory, we will approach different models of making decisions, including rational decision model, cognitive decision model, intuitive decision model, and mathematical model. Based on the understanding of how human should make a decision from those models, in the next topic about methodology to design of a computer supported system to support the decision making, we will systematically examine the process of design, and methods in constructing IDSS from multiple perspectives (decision maker, designers, social actors, etc.).
Lecturing and project work
The course will be lectured in English.
Students will work as project group (designer, user, mediator, leader) to design a concrete IDSS, e.g., investment decision support system.
Bai Guohua (1996) A Systems Approach to Decision Support Systems, Compendium, DSV, Luleå University (or http://www.ies.luth.se/~bai/iea005/DSS-slids/)
Turban E. And Aronson J. (1998) Decision Support Systems
and Intelligent Systems, Prentice-Hall International, Inc., London.
Active participating in Project work, seminar, and qualified project report: 1 point
Formal Examine: 2 points
To get pass to the course, you have to pass the two moments completely.
Experience in programming, e.g., Visual Basic, C, Excel, HTML etc. and mathematical model of Linear Programming (LP) are merits, but not a necessity.