623.131 (19S) Selected Topics in Artificial Intelligence

Sommersemester 2019

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Erster Termin der LV
12.06.2019 10:00 - 18:00 , S 1.45a
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Überblick

Lehrende/r
LV-Titel englisch
Selected Topics in Artificial Intelligence
LV-Art
Vorlesung-Kurs (prüfungsimmanente LV )
Semesterstunde/n
2.0
ECTS-Anrechungspunkte
4.0
Anmeldungen
13 (30 max.)
Organisationseinheit
Unterrichtssprache
Englisch
LV-Beginn
12.06.2019
eLearning
zum Moodle-Kurs

LV-Beschreibung

Inhalt/e

Reinforcement learning

How to find good sequences of decisions in an unknown domain through exploration and learning?

Stunning success of AlphaZero using reinforcement learning

Delayed rewards, long-term benefits of decisions, exploration and exploitation

Improving decision policy through exploration

Generalising what has been learned

Machine learning from noisy data

Problems with noise in learning data

Key ideas to cope with noise: paradoxically, simpler models are often better

Algorithms for learning decision trees from noisy data

How to estimate probabilities in machine learning correctly?

Argument-Based Machine Learning (ABML)

Human expert may help learning by annotating training examples with arguments

An algorithm for learning rules from argumented examples

ABML knowledge-elicitation loop

Learning qualitative models with applications in robotics

How to model qualitatively, avoiding numbers

Reasoning and simulation with qualitative models

Learning qualitative models from observations with QUIN and Pade

Learning and planning of robot tasks: rescue robot, humanoid robot, quadcopter

Learning from examples and background knowledge

How to use prior knowledge in Machine Learning?

Learning in logic – Inductive Logic Programming (ILP)

Learning programs from examples with ILP

Discovering problem structure with function decomposition

The idea of structuring the learning problem with function decomposition

Discovering structure with HINT algorithm

Improving accuracy and interpretability by structure learning in practice




Prüfungsinformationen

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) (Pflichtfach)
        • Ausgewählte Kapitel aus Artificial Intelligence ( 2.0h VK / 4.0 ECTS)
          • 623.131 Selected Topics in Artificial Intelligence (2.0h VC / 4.0 ECTS)
  • Masterstudium Angewandte Informatik (SKZ: 911, Version: 13W.1)
    • Fach: Knowledge and Data Engineering (Wahlfach)
      • Selected Topics in Artificial Intelligence ( 2.0h VK / 4.0 ECTS)
        • 623.131 Selected Topics in Artificial Intelligence (2.0h VC / 4.0 ECTS)

Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung

Sommersemester 2018
  • 623.131 VC Selected Topics in Machine Learning (2.0h / 4.0ECTS)
Sommersemester 2017
  • 623.131 VC Selected Topics in Artificial Intelligence (2.0h / 4.0ECTS)
Sommersemester 2016
  • 623.131 VC Selected Topics in Artificial Intelligence (2.0h / 4.0ECTS)
Sommersemester 2015
  • 623.131 VK Selected Topics in Artificial Intelligence (2.0h / 4.0ECTS)
Sommersemester 2014
  • 623.131 VK Selected Topics in Artificial Intelligence (2.0h / 4.0ECTS)
Sommersemester 2013
  • 623.131 VK Selected Topics in Artificial Intelligence (2.0h / 3.0ECTS)
Sommersemester 2012
  • 623.131 VK Selected Topics in Artificial Intelligence (2.0h / 3.0ECTS)
Sommersemester 2011
  • 623.131 VK Selected Topics in Artificial Intelligence (2.0h / 3.0ECTS)
Sommersemester 2010
  • 623.131 VK Selected Topics in Artificial Intelligence (2.0h / 4.0ECTS)
Sommersemester 2009
  • 623.131 VK Selected Topics in Artificial Intelligence (2.0h / 4.0ECTS)