Stud.IP Uni Oldenburg
University of Oldenburg
19.05.2022 23:23:27
inf530 - Artificial Intelligence (Complete module description)
Inf530 - Artificial Intelligence (Complete module description)
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Module label Artificial Intelligence
Module code inf530
Credit points 6.0 KP
Workload 180 h
Institute directory Department of Computing Science
Applicability of the module
  • Bachelor's Programme Business Informatics (Bachelor) > Akzentsetzungsbereich Praktische Informatik und Angewandte Informatik
  • Bachelor's Programme Computing Science (Bachelor) > Akzentsetzungsbereich - Wahlbereich Informatik
  • Master of Education Programme (Gymnasium) Computing Science (Master of Education) > Wahlpflichtmodule (Angewandte Informatik)
  • Master of Education Programme (Vocational and Business Education) Computing Science (Master of Education) > Akzentsetzungsbereich
Responsible persons
Sauer, Jürgen (Module responsibility)
Lehrenden, Die im Modul (Authorized examiners)
Prerequisites
Skills to be acquired in this module
The students are familiar with the basic concepts of artificial intelligence (AI). They know the concept of rational agents and their behavior. They know how to implement expert systems.They also know basic search and problem solving techniques as well as techniques of knowledge representation.
The students can compare different problem solving techniques and use them within other problem contexts.

Professional competence
The students:
  • describe the concept of rational agents and their behavior in an agent environemt
  • name and describe the basic search and problem solving techniques of Artificial Intelligence
  • describe and implement expert systems
  • describe basic techniques of knowledge representation


Methodological competence
The students:
  • acknowledge the basic methods of AI
  • transfer AI methods to other application areas
  • evaluate AI methods regarding their appropriateness for destinct problem areas
  • modify and adapt AI methods for specific application areas

Social competence
The students:
  • work in teams
  • present results to groups

Self-competence
The students:
  • reflect their results with regard to the methods of AI
Module contents
  • Overview of AI
  • Rational agents and agent based systems
  • Search and other problem solving techniques
  • Knowledge representation
  • Planning
Reader's advisory
  • Russel, S. J.: Norvig, Peter (2012): Artificial Intelligence: A modern Aproach, 3rd Ed.
  • Winston, P.H. (1994): Artificial Intelligence, 3rd Edition
Links
Language of instruction German
Duration (semesters) 1 Semester
Module frequency jährlich
Module capacity unlimited
Modullevel / module level AS (Akzentsetzung / Accentuation)
Modulart / typ of module je nach Studiengang Pflicht oder Wahlpflicht
Lehr-/Lernform / Teaching/Learning method V+Ü
Vorkenntnisse / Previous knowledge Grundkenntnisse Informatik/Wirtschaftsinformatik
Course type Comment SWS Frequency Workload of compulsory attendance
Exercises
2 SuSe 28
Lecture
2 SuSe 28
Total time of attendance for the module 56 h
Examination Time of examination Type of examination
Final exam of module
At the end of the lecture period
Written or oral exam