| General data | |
| Course Title | Decision support methods |
| ECTS credits | 6 |
| Course Code | |
| Type of Course | Compulsory |
| Year and Semester of Study | First year / Winter semester |
| Course Website | - |
| Department | Department of Informatics |
| Course Coordinator | Assistant Professor Nikola Vlahović, PhD |
| Instructors | Assistant Professor Nikola Vlahović, PhD |
| Assistants | - |
| Type of Degree Program | Graduate Study Programme |
| Major | - |
| Hours per Semester | 40 (20+10+10) |
| Language of Instruction | English |
| Class Schedule | Schedule |
| Course Contents | |
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1. Introduction to Decision support methods 2. Intelligent decision support methods 3. Expert systems and Knowledge based systems 4. Knowledge representation 5. Inference using knowledge 6. Knowledge engineering 7. Software agents 8. Multiagent systems and collaborative decision making support 9. Web and multimedia in decision support 10. Web intelligence and Semantic Web 11. Simulation modelling in decision support 12. Discrete-event simulation 13. Multiagent simulation 14. Software tools for decision support |
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| Description of general and specific competences (knowledge and skills) to be developed by this course: | |
| Students are introduced to methods, techniques and software tools for decision support. Competence is gained in recognition of business problems that can be solved by these methods. Students acquire specific knowledge about simulation modelling of dynamic business systems, expert systems and knowledge representation. The course is aimed at developing knowledge and skills related to development of expert systems for decision support. Students are trained to work in teams and acquire examples and knowledge from practice. | |
| Teaching methods: | |
| Lectures, seminars, exercises, project development and project presentation in teams. | |
| Additional requirements for students: | |
| Active participation in all forms of lecturing. Monitoring and reading of up-to-date literature. Internet-based research. Visiting companies as part of project development. | |
| Assessment/examination method: | |
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Students' knowledge will be evaluated in the course of contact hours (lectures, exercises, seminar work, tests). The final grade will be formed on the basis of continuous assessment and the written exam. Different forms of knowledge assessment are as follows: class participation 10%, team project evaluation 35%, seminar work 20%, written exam 35% of the final grade. |
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| Required reading: | |
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G. M. Marakas (2009), Decision Support Systems in the 21st Century. 2. edition, Prentice Hall. S. Russell, P. Norvig (2010), Artificial Intelligence: A Modern Approach, 3. edition, Prentice Hall. – selected chapters N. Vlahović, Computer Aided Decision Support (CADS), in preparation N. Vlahović, Knowledge Based Systems, Practical handbook, in preparation |
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| Recommended reading: | |
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W. Wooldridge (2009), Introduction to Multi Agent Systems, 2. Edition, Weily & Sons. – selected chapters M. Fasli (2007). Agent Technology for E-Commerce, Wiley & Sons. – selected chapters B. Edmonds, C. Hernandez, K. G. Treutzsch (2007). Social Simulation, IGI Global. – selected chapters N. Zong , L. Liu, Y. Yao (2010). Web Intelligence, Springer. – selected chapters A. Seila, V. Čerić i P. Tadikamalla (2003), Applied Simulation Modeling, Thomson - Brooks/Cole. |
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| Course and teaching quality assurance method (method of monitoring the quality of the course and its teaching): | |
| Internal evaluation by anonymous student survey at the end of the course. | |
| Course Prerequisites | |
| - | |
| Additional Information | |
| - | |