621.065 (14W) Uncertain Knowledge: Reasoning and Learning

Wintersemester 2014/15

Registration deadline has expired.

First course session
06.10.2014 10:00 - 12:00 S.1.42 On Campus
... no further dates known

Overview

Lecturer
Course title german Uncertain Knowledge: Reasoning and Learning
Type Lecture - Colloquia (continuous assessment course )
Hours per Week 2.0
ECTS credits 4.0
Registrations 27 (25 max.)
Organisational unit
Language of instruction English
Course begins on 01.10.2014

Time and place

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Course Information

Teaching methodology including the use of eLearning tools

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

Course content

Provides an introduction to Artificial Intelligence and Knowledge-Based Systems. This lecture corresponds to the Knowledge Engineering practice in WS 13.

Topics

  • 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

Teaching objective

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

Prior knowledge expected

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.

Literature

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

Teaching methodology including the use of eLearning tools

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

Course content

Provides an introduction to Artificial Intelligence and Knowledge-Based Systems

Topics

  • 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

Teaching objective

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

Prior knowledge expected

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.

Literature

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

Examination information

Im Fall von online durchgeführten Prüfungen sind die Standards zu beachten, die die technischen Geräte der Studierenden erfüllen müssen, um an diesen Prüfungen teilnehmen zu können.

Examination topic(s)

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

Assessment criteria / Standards of assessment for examinations

Written examination

Examination topic(s)

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

Assessment criteria / Standards of assessment for examinations

Written examination

Grading scheme

Grade / Grade grading scheme

Position in the curriculum

  • Teacher training programme Computer Sciences and Computer Sciences Management (Secondary School Teacher Accreditation) (SKZ: 884, Version: 04W.7)
    • Stage two
      • Subject: Angewandte Informatik (LI 2.3) (Compulsory subject)
        • Knowledge Engineering ( 2.0h PR / 4.0 ECTS)
          • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VK / 4.0 ECTS)
  • Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 12W.1)
    • Subject: Media Informatics (Compulsory elective)
      • Knowledge Engineering ( 2.0h UE / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VK / 4.0 ECTS)
  • Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 12W.1)
    • Subject: Natural Language Processing (Compulsory elective)
      • Knowledge Engineering ( 2.0h UE / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VK / 4.0 ECTS)
  • Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 12W.1)
    • Subject: Software Development (Compulsory elective)
      • Knowledge Engineering ( 2.0h UE / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VK / 4.0 ECTS)
  • Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 12W.1)
    • Subject: Business Informatics (Compulsory elective)
      • Knowledge Engineering ( 2.0h UE / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VK / 4.0 ECTS)
  • Bachelorstudium Informatik (SKZ: 521, Version: 09W.3)
    • Subject: Knowledge Engineering (Compulsory elective)
      • Knowledge Engineering ( 2.0h PR / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VK / 4.0 ECTS)
  • Bachelor's degree programme Informatics (SKZ: 521, Version: 03W.1)
    • Subject: Knowledge Engineering (Compulsory subject)
      • Knowledge Engineering ( 2.0h PR / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VK / 4.0 ECTS)
  • Master's degree programme Applied Informatics (SKZ: 911, Version: 13W.1)
    • Subject: Vertiefung Informatik (Compulsory subject)
      • Knowledge Engineering ( 2.0h UE / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VK / 4.0 ECTS)
  • Masterstudium Informatik (SKZ: 921, Version: 09W.1)
    • Subject: Knowledge Engineering (Compulsory elective)
      • Knowledge Engineering ( 2.0h PR / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VK / 4.0 ECTS)
  • Bachelor's degree programme Technical Mathematics (SKZ: 201, Version: 12W.2)
    • Subject: Informatik (Compulsory elective)
      • Knowledge Engineering ( 2.0h UE / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VK / 4.0 ECTS)
  • Master's degree programme Technical Mathematics (SKZ: 401, Version: 13W.1)
    • Subject: Informatik (Compulsory elective)
      • Knowledge Engineering ( 2.0h UE / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VK / 4.0 ECTS)

Equivalent courses for counting the examination attempts

Sommersemester 2019
  • 621.065 VC Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)
Wintersemester 2018/19
  • 621.065 VC Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)
Sommersemester 2018
  • 621.065 VC Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)
Wintersemester 2017/18
  • 621.065 VC Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)
Sommersemester 2017
  • 621.065 VC Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)
Wintersemester 2016/17
  • 621.065 VC Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)
Sommersemester 2016
  • 621.065 VC Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)
Wintersemester 2015/16
  • 621.065 VC Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)
  • 621.066 VC Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)
Sommersemester 2015
  • 621.065 VK Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)