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Decision Support Systems

Module name (EN):
Name of module in study programme. It should be precise and clear.
Decision Support Systems
Degree programme:
Study Programme with validity of corresponding study regulations containing this module.
Computer Science and Communication Systems, Bachelor, ASPO 01.10.2014
Module code: KI650
Hours per semester week / Teaching method:
The count of hours per week is a combination of lecture (V for German Vorlesung), exercise (U for Übung), practice (P) oder project (PA). For example a course of the form 2V+2U has 2 hours of lecture and 2 hours of exercise per week.
4V (4 hours per week)
ECTS credits:
European Credit Transfer System. Points for successful completion of a course. Each ECTS point represents a workload of 30 hours.
Semester: 6
Mandatory course: no
Language of instruction:
Written exam (50 %) / Student assignment (50 %)

[updated 20.03.2007]
Applicability / Curricular relevance:
All study programs (with year of the version of study regulations) containing the course.

KI650 Computer Science and Communication Systems, Bachelor, ASPO 01.10.2014 , semester 6, optional course
Workload of student for successfully completing the course. Each ECTS credit represents 30 working hours. These are the combined effort of face-to-face time, post-processing the subject of the lecture, exercises and preparation for the exam.

The total workload is distributed on the semester (01.04.-30.09. during the summer term, 01.10.-31.03. during the winter term).
60 class hours (= 45 clock hours) over a 15-week period.
The total student study time is 150 hours (equivalent to 5 ECTS credits).
There are therefore 105 hours available for class preparation and follow-up work and exam preparation.
Recommended prerequisites (modules):
Recommended as prerequisite for:
Module coordinator:
Prof. Dave Swayne
Prof. Dave Swayne

[updated 01.04.2003]
Learning outcomes:
After completing this course students will understand agent architectures in artificial intelligence and the relationship between artificial intelligence and operations research (planning and decision making).
Students will be able to distinguish between three different classes of decision-making systems (logic-based, probabilistic and machine-learning-based) and will gain experience with a sample of each of the following system classes: first-order logic / prolog, Bayesian network, inductive learning / decision tree.

[updated 13.03.2007]
Module content:
Artificial intelligence (introduction, intelligent agents)
Problem-solving (solving problems by searching)
Knowledge and reasoning (agents, logic, Prolog)
Acting logically (planning)
Uncertain knowledge and reasoning (uncertainty, probabilistic reasoning, decisions)
Expert systems based on machine learning

[updated 13.03.2007]
Recommended or required reading:
Artificial Intelligence A Modern Approach, Second Edition, Stewart Russell and Peter Norvig

[updated 13.03.2007]
Module offered in:
WS 2005/06, SS 2005
[Mon Jun 24 08:51:39 CEST 2024, CKEY=dss, BKEY=ki, CID=KI650, LANGUAGE=en, DATE=24.06.2024]