623.614 (18W) Current Topics in Artificial Intelligence

Wintersemester 2018/19

Anmeldefrist abgelaufen.

Erster Termin der LV
22.11.2018 09:00 - 12:15 , S.1.42
... keine weiteren Termine bekannt

Überblick

Lehrende/r
LV-Titel englisch
Current Topics in Artificial Intelligence
LV-Art
Vorlesung-Kurs (prüfungsimmanente LV )
Semesterstunde/n
2.0
ECTS-Anrechungspunkte
4.0
Anmeldungen
16 (24 max.)
Organisationseinheit
Unterrichtssprache
Englisch
mögliche Sprache/n der Leistungserbringung
Englisch
LV-Beginn
22.11.2018
eLearning
zum Moodle-Kurs

LV-Beschreibung

Intendierte Lernergebnisse

At the end of the course, the students shall understand the benefits of various forms of product configuration and their embedding in Product Lifecycle Management and be able to select and use appropriate tools to find solutions for configuration requirements arising in practice.

Inhalt/e

Overview

Who needs configuration (i.e. individualization of products and services) and what for?

Typical examples from long-time experience with configuring complex technical systems.

Key technologies and useful tools for tackling product configuration problems.

Topics

What is product configuration? Real-word examples from mass customization to engineer-to-order.

Modelling of knowledge bases (product variability, constraints, logic), debugging and testing.

User interaction and use cases (check, solve, optimize, reconfigure).

Constraint Satisfaction Problem and variants (GCSP), Constraint Optimizing Problem.

Algorithms and performance: e.g. pre-compilation, local search, symmetry breaking.

Diagnosis of inconsistent configurations and knowledge bases.

Practical work with open-source tools having different strengths:

S.P.L.O.T - an online feature modelling tool

MiniZinc (alternatively Choco) - a classical constraint solver with a standard syntax

Potassco - an open-source toolset based on logic (ASP - answer set programming)

Erwartete Vorkenntnisse

Basic knowledge in knowledge and data engineering, logic programming, and Java.

Preparation by reading some information on tools before the course.

Presence during all 4 days (with your own notebook)!

Prüfungsinformationen

Beurteilungsschema

Note/Grade Benotungsschema

Position im Curriculum

  • Masterstudium Angewandte Informatik (SKZ: 911, Version: 13W.1)
    • Fach: Business Information Systems (Wahlfach)
      • Topics in Knowledge and Data Engineering for Business Information Systems ( 2.0h VK / 4.0 ECTS)
        • 623.614 Current Topics in Artificial Intelligence (2.0h VC / 4.0 ECTS)
  • Masterstudium Angewandte Informatik (SKZ: 911, Version: 13W.1)
    • Fach: Knowledge and Data Engineering (Wahlfach)
      • Current Topics in Artificial Intelligence ( 2.0h VK / 4.0 ECTS)
        • 623.614 Current Topics in Artificial Intelligence (2.0h VC / 4.0 ECTS)
  • Masterstudium Informatik (SKZ: 921, Version: 09W.1)
    • Fach: Data and Knowledge Engineering (Pflichtfach)
      • Artificial Intelligence ( 2.0h VK / 4.0 ECTS)
        • 623.614 Current Topics in Artificial Intelligence (2.0h VC / 4.0 ECTS)
  • Masterstudium Informationsmanagement (SKZ: 922, Version: 13W.2)
    • Fach: Informationssysteme (Pflichtfach)
      • 2.8 Current Topics in Information Systems ( 2.0h SE/VC/KS / 4.0 ECTS)
        • 623.614 Current Topics in Artificial Intelligence (2.0h VC / 4.0 ECTS)

Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung

Diese Lehrveranstaltung ist keiner Kette zugeordnet