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10. Lernen durch Verstärkung (Reinforcement Learning)

  • 2025
  • OriginalPaper
  • Chapter
Published in:
Author
Wolfgang Ertel
Published in
Grundkurs Künstliche Intelligenz
Publisher
Springer Fachmedien Wiesbaden

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Zusammenfassung

Beim Lernen mit Lehrer werden immer gelabelte Daten benötigt. Wenn diese nicht vorhanden sind, wie etwa wenn ein Roboter das Greifen lernen soll, dann bleibt nur noch das Lernen durch Verstärkung. Das heißt, der Roboter optimiert seine Motorik mittels Versuch und Irrtum, basierend auf positiver und negativer Verstärkung. Einige einfach derartige Algorithmen und deren Anwendung werden hier vorgestellt.

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previous chapter Neuronale Netze
next chapter Lösungen zu den Übungen
Title
Lernen durch Verstärkung (Reinforcement Learning)
Author
Wolfgang Ertel
Copyright Year
2025
Book
Grundkurs Künstliche Intelligenz

Print ISBN: 978-3-658-44954-4

Electronic ISBN: 978-3-658-44955-1

Copyright Year: 2025

DOI
https://doi.org/10.1007/978-3-658-44955-1_10
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