Reinforcement Learning
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Reinforcement Learning

Reinforcement Learning


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About the Book

In uralten Spielen wie Schach oder Go können sich die brillantesten Spieler verbessern, indem sie die von einer Maschine produzierten Strategien studieren. Robotische Systeme üben ihre Bewegungen selbst. In Arcade Games erreichen lernfähige Agenten innerhalb weniger Stunden übermenschliches Niveau. Wie funktionieren diese spektakulären Algorithmen des bestärkenden Lernens? Mit gut verständlichen Erklärungen und übersichtlichen Beispielen in Java und Greenfoot können Sie sich die Prinzipien des bestärkenden Lernens aneignen und in eigenen intelligenten Agenten anwenden. Greenfoot (M.Kölling, King's College London) und das Hamster-Modell (D.Bohles, Universität Oldenburg) sind einfache, aber auch mächtige didaktische Werkzeuge, die entwickelt wurden, um Grundkonzepte der Programmierung zu vermitteln. Wir werden Figuren wie den Java-Hamster zu lernfähigen Agenten machen, die eigenständig ihre Umgebung erkunden. Die zweite Auflage enthält neue Themen wie "Genetische Algorithmen" und "Künstliche Neugier" sowie Korrekturen und Überarbeitungen.


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Product Details
  • ISBN-13: 9783662683101
  • Publisher: Springer
  • Binding: Paperback
  • Language: German
  • Returnable: Y
  • Sub Title: Aktuelle Ansätze Verstehen - Mit Beispielen in Java Und Greenfoot
  • Width: 170 mm
  • ISBN-10: 3662683105
  • Publisher Date: 06 May 2024
  • Height: 244 mm
  • No of Pages: 182
  • Spine Width: 12 mm
  • Weight: 412 gr


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Reinforcement Learning
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