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This entry is from Winter semester 2016/17 and might be obsolete. You can find a current equivalent here.

CS 592 — Artificial Intelligence
(dt. Künstliche Intelligenz)

Level, degree of commitment Specialization module, depends on importing study program
Forms of teaching and learning,
workload		 Lecture (2 SWS), recitation class (2 SWS),
180 hours (60 h attendance, 120 h private study)
Credit points,
formal requirements		 6 CP
Course requirement(s): Oral or written examination
Examination type: Successful completion of at least 50 percent of the points from the weekly exercises as well as at least 2 presentations of the tasks.
Language,
Grading		 German,
The grading is done with 0 to 15 points according to the examination regulations for the degree program M.Sc. Computer Science.
Subject, Origin Computer Science, M.Sc. Computer Science
Duration,
frequency		 One semester,
Jedes zweite Wintersemester
Person in charge of the module's outline Prof. Dr. Alfred Ultsch

Contents

  • Programming in Prolog/ Predicate Logic /Constraints
  • Knowledge, knowledge representation, inference
  • Structure of knowledge-based systems
  • Probability-based closing
  • DS and Fuzzy Inference
  • Knowledge Engineering and Machine Learning
  • Non-classical Logics
  • Practice of knowledge-based systems/agent systems

Qualification Goals

Students should

  • Become familiar with skills and knowledge of the main AI methods and their application in practice.
  • Be able to create knowledge-based inference systems, in predicate logic (Prolog).
  • Be able to use knowledge representation forms,
  • have knowledge of problem solving, search and planning algorithms,
  • have an overview of common methods of estimation: Bayes, Demster/Shafer, Fuzzy Inference possess,
  • know methods of knowledge acquisition from the field of machine learning and knowledge engineering,
  • have an insight into non-classical logics,
  • practice scientific working methods (recognizing, formulating, solving problems, training the ability of abstraction)
  • practice oral communication skills in the exercises by practicing free speech in front of an audience

Prerequisites

Translation is missing. Here is the German original:

Keine. Empfohlen werden die Kompetenzen aus den Basismodulen zur Informatik und Knowledge Discovery.


Recommended Reading

  • W.F. Clocksin, C.S. Mellish: Programming in Prolog, Springer, 2003.
  • S. Russell, P. Norvig. Artificial Intelligence: A Modern Approach. Prentice Hall, 2002.



Please note:

This page describes a module according to the latest valid module guide in Winter semester 2016/17. Most rules valid for a module are not covered by the examination regulations and can therefore be updated on a semesterly basis. The following versions are available in the online module guide:

The module guide contains all modules, independent of the current event offer. Please compare the current course catalogue in Marvin.

The information in this online module guide was created automatically. Legally binding is only the information in the examination regulations (Prüfungsordnung). If you notice any discrepancies or errors, we would be grateful for any advice.