DECISION SUPPORT THEORY AND SYSTEMS
| Title | ΘΕΩΡΙΑ ΚΑΙ ΣΥΣΤΗΜΑΤΑ ΛΗΨΗΣ ΑΠΟΦΑΣΕΩΝ / DECISION SUPPORT THEORY AND SYSTEMS |
| Code | NIS-06-01 |
| Faculty | Sciences |
| School | Informatics |
| Cycle / Level | 1st / Undergraduate |
| Teaching Period | Spring |
| Coordinator | Ioannis Vlachavas |
| Common | No |
| Status | Active |
| Course ID | 40002949 |
Programme of Study: PPS-Tmīma Plīroforikīs (2019-sīmera)
Registered students: 44
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| GENIKĪ KATEUTHYNSĪ | YPOCΗREŌTIKO KATA EPILOGĪ | 6 | 3 | 5 |
| Academic Year | 2018 – 2019 |
| Class Period | Spring |
| Faculty Instructors |
|
| Weekly Hours | 3 |
| Class ID | 600121323
|
Course Type 2016-2020
- Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600121323
- eLearning (Moodle): http://pileas.csd.auth.gr
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
- Greek (Instruction, Examination)
Prerequisites
General Prerequisites
Basic knowledge of probability theory.
Learning Outcomes
Cognitive:
Understanding the basic theory for simple and sequential decisions by an intelligent agent, familiarization with the types of decision support systems, understanding the theory of decision making with data analysis, understanding the basic principles of game theory, understanding computational issues in developing decision support systems, familiarization with the use of decision support software.
Skills:
Training on developing decision support systems, training on the use of decision support tools.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Adapt to new situations
- Make decisions
- Work autonomously
- Advance free, creative and causative thinking
Course Content (Syllabus)
Introduction, Decision Making under Certainty (Multi-criteria Decision Making Methods), Decision Making under Ignorance, Decision Making under Risk (Probability Theory, Bayesian Networks, Utility Theory), Sequential Decisions (Decision Trees, Markov Decision Processes, Dynamic Programming), Decision Making in the presence of Competitive Agents (Game Theory), Decision Making with Data Analysis (Machine Learning, Knowledge Discovery in Databases).
Educational Material Types
- Notes
- Slide presentations
- Book
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Communication with Students
- Use of ICT in Student Assessment
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 52 | ✓ | |||
| Reading Assigment | 85 | ✓ | |||
| Written assigments | 10 | ✓ | |||
| Exams | 3 | ✓ | |||
| Total | 150 |
Student Assessment
Description
Final Exams (at the end of the semester). Quizes with multiple choice questions. Bonus grades from projects. The evaluation criteria are mentioned in the course webpages.
Student Assessment methods
- Written Exam with Multiple Choice Questions (Summative)
- Written Exam with Short Answer Questions (Summative)
- Written Exam with Extended Answer Questions (Summative)
- Written Assignment (Summative)
- Written Exam with Problem Solving (Summative)
Bibliography
Course Bibliography (Eudoxus)
i) Τεχνητή Νοημοσύνη: Μια σύγχρονη προσέγγιση, S Russel, P. Norvig, ΚΛΕΙΔΑΡΙΘΜΟΣ, ISBN: 9602098732,
ii)Τεχνητή Νοημοσύνη, Ι. Βλαχάβας, Π. Κεφαλάς, Ν. Βασιλειάδης, Φ. Κόκκορας, Η. Σακελλαρίου, Γ' Έκδοση, Εκδόσεις Πανεπιστημίου Μακεδονίας, 2011, ISBN: 978-960-8396-64-7
Additional bibliography for study
Σημειώσεις μαθήματος σε ηλεκτρονική μορφή
Διαφάνειες μαθήματος σε ηλεκτρονική μορφή
Last Update
15-06-2016
