621.061 (23W) Introduction to Artificial Intelligence I - Group A

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Wintersemester 2023/24

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First course session
05.10.2023 16:00 - 18:00 On Campus

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Overview

Lecturer

O.Univ.-Prof. Dipl.-Ing. Dr. Gerhard Friedrich

Course title german

Introduction to Artificial Intelligence 1 - Group A

Type

Lecture - Course (continuous assessment course )

Course model

Blended learning course

Online proportion

30%

Hours per Week

2.0

ECTS credits

3.0

Registrations

37 (30 max.)

Organisational unit

Institut für Artificial Intelligence und Cybersecurity

Language of instruction

Englisch

Course begins on

05.10.2023

eLearning

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Time and place

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Intended learning outcomes

Provides an introduction to general problem solving methods used in artificial intelligence and knowledge-based systems. The course presents a variety of search approaches as well as modern knowledge representation and reasoning systems implementing them.

Teaching methodology including the use of eLearning tools

Classroom instructions mixed with practical exercises. The teaching language is English or German depending on the preferences of the audience. The slides are in English.

Course content

Covered topics include:

Uninformed and informed search methods
Overview of incomplete (local) approaches to solving hard problems
Knowledge representation and reasoning with constraints programming
MiniZinc programming language
Game playing

Prior knowledge expected

Algorithms and data structures

Curricular registration requirements

Nothing

Literature

Stefan Edelkamp and Stefan Schrödl: Heuristic search: theory and applications. Elsevier, 2011
Rina Dechter: Constraint Processing. Morgan Kaufmann Publishers, 2003
Stefan Edelkamp and Stefan Schrödl: Heuristic search: theory and applications. Elsevier, 2012

Intended learning outcomes

Teaching methodology including the use of eLearning tools

Classroom instructions mixed with practical exercises. The teaching language is English or German depending on the preferences of the audience. The slides are in English.

Course content

Covered topics include:

Uninformed and informed search methods
Overview of incomplete (local) approaches to solving hard problems
Knowledge representation and reasoning with constraints programming
MiniZinc programming language
Game playing

Prior knowledge expected

Algorithms and data structures

Curricular registration requirements

Nothing

Literature

Stefan Edelkamp and Stefan Schrödl: Heuristic search: theory and applications. Elsevier, 2011
Rina Dechter: Constraint Processing. Morgan Kaufmann Publishers, 2003
Stefan Edelkamp and Stefan Schrödl: Heuristic search: theory and applications. Elsevier, 2012

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.

German
English

Examination methodology

Mini tests, written and oral examinations

Examination topic(s)

Uninformed and informed search methods
Overview of incomplete (local) approaches to solving hard problems
Knowledge representation and reasoning with constraints programming
MiniZinc programming language
Game playing

Assessment criteria / Standards of assessment for examinations

The final grade is positive if and only if:
- >= 50% of all mini test points are reached.
- >= 40 % in the written exam are reached.
- The oral examination is positive.
Based on the oral examination, the final grading is set.

Examination methodology

Mini tests, written and oral examinations

Examination topic(s)

Uninformed and informed search methods
Overview of incomplete (local) approaches to solving hard problems
Knowledge representation and reasoning with constraints programming
MiniZinc programming language
Game playing

Assessment criteria / Standards of assessment for examinations

The final grade is positive if and only if:
- >= 50% of all mini test points are reached.
- >= 40 % in the written exam are reached.
- The oral examination is positive.
Based on the oral examination, the final grading is set.

Grading scheme

Grade / Grade grading scheme

Position in the curriculum

Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 19W.2)
- Subject: Vertiefung Informatik (Compulsory elective)
  - 7.3 Einführung in die Artificial Intelligence I ( 2.0h VC / 3.0 ECTS)
    - 621.061 Introduction to Artificial Intelligence I - Group A (2.0h VC / 3.0 ECTS)
      Absolvierung im 4., 5., 6. Semester empfohlen

Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 17W.1)
- Subject: Medieninformatik (Compulsory elective)
  - 4.1 Heuristic Search ( 2.0h VC / 2.0 ECTS)
    - 621.061 Introduction to Artificial Intelligence I - Group A (2.0h VC / 2.0 ECTS)

Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 17W.1)
- Subject: Natural Language Processing (Compulsory elective)
  - 5.2 Heuristic Search ( 2.0h VC / 2.0 ECTS)
    - 621.061 Introduction to Artificial Intelligence I - Group A (2.0h VC / 2.0 ECTS)

Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 17W.1)
- Subject: Software Development (Compulsory elective)
  - 6.2 Heuristic Search ( 2.0h VC / 2.0 ECTS)
    - 621.061 Introduction to Artificial Intelligence I - Group A (2.0h VC / 2.0 ECTS)

Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 17W.1)
- Subject: Business Informatics (Compulsory elective)
  - 7.2 Heuristic Search ( 2.0h VC / 2.0 ECTS)
    - 621.061 Introduction to Artificial Intelligence I - Group A (2.0h VC / 2.0 ECTS)

Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 12W.1)
- Subject: Media Informatics (Compulsory elective)
  - Knowledge Engineering ( 2.0h VO / 2.0 ECTS)
    - 621.061 Introduction to Artificial Intelligence I - Group A (2.0h VC / 2.0 ECTS)

Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 12W.1)
- Subject: Natural Language Processing (Compulsory elective)
  - Knowledge Engineering ( 2.0h VO / 2.0 ECTS)
    - 621.061 Introduction to Artificial Intelligence I - Group A (2.0h VC / 2.0 ECTS)

Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 12W.1)
- Subject: Software Development (Compulsory elective)
  - Knowledge Engineering ( 2.0h VO / 2.0 ECTS)
    - 621.061 Introduction to Artificial Intelligence I - Group A (2.0h VC / 2.0 ECTS)

Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 12W.1)
- Subject: Business Informatics (Compulsory elective)
  - Knowledge Engineering ( 2.0h VO / 2.0 ECTS)
    - 621.061 Introduction to Artificial Intelligence I - Group A (2.0h VC / 2.0 ECTS)

Master's degree programme Applied Informatics (SKZ: 911, Version: 13W.1)
- Subject: Vertiefung Informatik (Compulsory subject)
  - Knowledge Engineering ( 2.0h VO / 2.0 ECTS)
    - 621.061 Introduction to Artificial Intelligence I - Group A (2.0h VC / 2.0 ECTS)

Bachelor's degree programme Management Information Systems (SKZ: 522, Version: 20W.2)
- Subject: Spezialisierung Angewandte Informatik (Compulsory elective)
  - Spezialisierung Angewandte Informatik ( 0.0h VO, VC, KS, UE / 6.0 ECTS)
    - 621.061 Introduction to Artificial Intelligence I - Group A (2.0h VC / 3.0 ECTS)
      Absolvierung im 6. Semester empfohlen

Bachelor's degree programme Robotics and Artificial Intelligence (SKZ: 295, Version: 22W.1)
- Subject: Artificial Intelligence (Compulsory subject)
  - 4.1 Introduction to Artificial Intelligence I ( 2.0h VC / 3.0 ECTS)
    - 621.061 Introduction to Artificial Intelligence I - Group A (2.0h VC / 3.0 ECTS)

Equivalent courses for counting the examination attempts

Sommersemester 2024

621.061 VC Introduction to Artificial Intelligence 1 - Group A (2.0h / 3.0ECTS)
621.063 VC Introduction to Artificial Intelligence 1 - Group B (2.0h / 3.0ECTS)

Wintersemester 2023/24

621.063 VC Introduction to Artificial Intelligence 1 - Group B (2.0h / 3.0ECTS)
621.065 VC Introduction to Artificial Intelligence 1 - Group C (2.0h / 3.0ECTS)

Sommersemester 2023

621.061 VC Einführung in die Artificial Intelligence I (2.0h / 3.0ECTS)

Wintersemester 2022/23

621.061 VC Einführung in die Artificial Intelligence I (2.0h / 3.0ECTS)

Sommersemester 2022

621.061 VC Einführung in die Artificial Intelligence I (2.0h / 3.0ECTS)

Wintersemester 2021/22

621.061 VC Einführung in die Artificial Intelligence I (2.0h / 3.0ECTS)

Sommersemester 2021

621.061 VC Einführung in die Artificial Intelligence I (2.0h / 3.0ECTS)

Wintersemester 2020/21

621.061 VC Einführung in die Artificial Intelligence I (2.0h / 3.0ECTS)

Sommersemester 2020

621.061 VC Einführung in die Artificial Intelligence I (2.0h / 3.0ECTS)

Wintersemester 2019/20

621.061 VC Einführung in die Artificial Intelligence I (2.0h / 3.0ECTS)