621.050 (08W) Knowledge Engineering

Wintersemester 2008/09

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Überblick

Lehrende/r
LV-Titel englisch
LV-Art
Vorlesung
Semesterstunde/n
2.0
ECTS-Anrechungspunkte
2.0
Anmeldungen
63
Organisationseinheit
Unterrichtssprache
Deutsch
LV-Beginn
07.10.2008
eLearning
zum Moodle-Kurs

Zeit und Ort

Tag von - bis Raum Details
Di, 07.10.2008 16:00 - 18:00 E.2.42 wöchentlich
Di, 14.10.2008 16:00 - 18:00 E.2.42 wöchentlich
Di, 21.10.2008 16:00 - 18:00 E.2.42 wöchentlich
Di, 28.10.2008 16:00 - 18:00 E.2.42 wöchentlich
Di, 04.11.2008 16:00 - 18:00 E.2.42 wöchentlich
Di, 11.11.2008 16:00 - 18:00 E.2.42 wöchentlich
Di, 18.11.2008 16:00 - 18:00 E.2.42 wöchentlich
Di, 25.11.2008 16:00 - 18:00 E.2.42 wöchentlich
Di, 02.12.2008 16:00 - 18:00 E.2.42 wöchentlich
Mi, 03.12.2008 09:00 - 12:00 HS 7 Einzeltermin
Di, 09.12.2008 16:00 - 18:00 E.2.42 wöchentlich
Di, 16.12.2008 16:00 - 18:00 E.2.42 wöchentlich
Di, 13.01.2009 16:00 - 18:00 E.2.42 wöchentlich
Di, 20.01.2009 16:00 - 18:00 E.2.42 wöchentlich
Di, 27.01.2009 16:00 - 18:00 E.2.42 wöchentlich

LV-Beschreibung

Lehrmethodik

Classroom instructions supported by associated lab course. The teaching language is English or German depending on the preferences of the audience.

Inhalt/e

Provides an introduction to Artificial Intelligence and Knowledge-Based Systems

Themen

  • Introduction
  • Intelligent agents
  • Solving problems by searching
  • Informed search and exploration
  • Constraint satisfaction problems
  • Adversarial search
  • Knowledge representation and reasoning
  • Planning
  • Uncertain knowledge and reasoning
  • Learning
  • Methods for selected application areas

Schlagworte

Artificial Intelligence, Knowledge-Based Systems

Lehrziel

Acquiring the capability to design and implement software systems exploiting methods of Artificial Intelligence

Erwartete Vorkenntnisse keine Anmeldevoraussetzung

The course builds on knowledge about propositional and predicate logic as well as logical inference techniques. These topics are typically covered by courses on Logic and Logic Programming.

Literatur

Stuart Russell and Peter Norvig: Artificial Intelligence, A modern approach, Prentice Hall, 2003 Georg Gottlob, Thomas Frühwirth, Werner Horn (Hrsg.): Expertensysteme, Springer Verlag, 1990 Ivan Bratko: Prolog ‑ Programming for Artificial Intelligence, Addison‑Wesley, 1990

Lehrmethodik

Classroom instructions supported by associated lab course. The teaching language is English or German depending on the preferences of the audience.

Inhalt/e

Provides an introduction to Artificial Intelligence and Knowledge-Based Systems

Themen

  • Introduction
  • Intelligent agents
  • Solving problems by searching
  • Informed search and exploration
  • Constraint satisfaction problems
  • Adversarial search
  • Knowledge representation and reasoning
  • Planning
  • Uncertain knowledge and reasoning
  • Learning
  • Methods for selected application areas

Schlagworte

Artificial Intelligence, Knowledge-Based Systems

Lehrziel

Acquiring the capability to design and implement software systems exploiting methods of Artificial Intelligence

Erwartete Vorkenntnisse keine Anmeldevoraussetzung

The course builds on knowledge about propositional and predicate logic as well as logical inference techniques. These topics are typically covered by courses on Logic and Logic Programming.

Literatur

Stuart Russell and Peter Norvig: Artificial Intelligence, A modern approach, Prentice Hall, 2003 Georg Gottlob, Thomas Frühwirth, Werner Horn (Hrsg.): Expertensysteme, Springer Verlag, 1990 Ivan Bratko: Prolog ‑ Programming for Artificial Intelligence, Addison‑Wesley, 1990

Prüfungsinformationen

Prüfungsinhalt/e

Topics covered in the course including selected chapters of the mentioned literature

Beurteilungskriterien/-maßstäbe

Written examination

Prüfungsinhalt/e

Topics covered in the course including selected chapters of the mentioned literature

Beurteilungskriterien/-maßstäbe

Written examination

Beurteilungsschema

Note/Grade Benotungsschema

Position im Curriculum

  • Lehramtsstudium Unterrichtsfach Informatik und Informatikmanagement (SKZ: 884, Version: 04W.7)
    • 2.Abschnitt
      • Fach: Angewandte Informatik (LI 2.3)
        • Knowledge Engineering ( 2.0h VO / 2.0 ECTS)
          • 621.050 Knowledge Engineering (2.0h VO / 2.0 ECTS)
  • Bachelorstudium Informatik (SKZ: 521, Version: 03W.1)
    • Fach: Knowledge Engineering
      • Knowledge Engineering ( 2.0h VO / 2.0 ECTS)
        • 621.050 Knowledge Engineering (2.0h VO / 2.0 ECTS)
  • Masterstudium Informatik (SKZ: 921, Version: 03W.1)
    • Fach: Knowledge Engineering
      • Knowledge Engineering ( 2.0h VO / 2.0 ECTS)
        • 621.050 Knowledge Engineering (2.0h VO / 2.0 ECTS)
  • Diplomstudium Informatik (SKZ: 880, Version: 02W)
    • 2.Abschnitt
      • Fach: Angewandte Informatik inkl. Vertiefungsfach
        • Knowledge Engineering ( 2.0h VO / 2.0 ECTS)
          • 621.050 Knowledge Engineering (2.0h VO / 2.0 ECTS)

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