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Belohnen Und Lernen: Praktisches Reinforcement Learning für autonome Agenten, Spiele und Robotersteuerung
Paperback
Publisher: Independently Published
Published: Jul 16 2026
Pages: 306
Weight: 0.82
Height: 0.76 Width: 6.00 Depth: 9.00
Language: German
BELOHNEN UND LERNEN ist ein praxisorientierter Leitfaden für Entwickler, Data Scientists, KI-Ingenieure und Robotikexperten, die Reinforcement Learning (verstärkendes Lernen) verstehen und auf reale Anwendungen übertragen möchten.
Im Gegensatz zu klassischen Machine-Learning-Methoden lernen Reinforcement-Learning-Systeme durch Interaktion, Feedback und Belohnungen. Diese Fähigkeit bildet die Grundlage für autonome Agenten, intelligente Spiele-KI und adaptive Robotersysteme.
Dieses Buch zeigt, wie lernende Agenten entwickelt werden - von den mathematischen Grundlagen bis hin zu praktischen Implementierungen mit modernen Python-Werkzeugen.
Du lernst unter anderem:
- Wie Reinforcement Learning und Entscheidungsprozesse funktionieren
- Wie Agenten, Umgebungen, Zustände und Belohnungen modelliert werden
- Wie Q-Learning und moderne Deep-Reinforcement-Learning-Verfahren eingesetzt werden
- Wie neuronale Netze für intelligente Agenten genutzt werden
- Wie autonome Systeme durch Erfahrung lernen und sich verbessern
- Wie Reinforcement Learning in Spielen und Simulationen angewendet wird
- Wie Robotersteuerungen mit lernenden Algorithmen entwickelt werden
- Wie KI-Agenten getestet, optimiert und in realen Anwendungen eingesetzt werden
Praxisnahe Beispiele, verständliche Erklärungen und reale Anwendungsszenarien verbinden Theorie und Umsetzung, sodass du eigene intelligente Agenten entwickeln kannst.
Ob autonome Roboter, Spiele-KI, Simulationen oder intelligente Automatisierungssysteme - dieses Buch vermittelt die Fähigkeiten, um lernende Systeme aufzubauen, die eigenständig Entscheidungen treffen und sich kontinuierlich verbessern.
BELOHNEN UND LERNEN - Der umfassende Leitfaden für praktisches Reinforcement Learning, autonome Agenten und intelligente Steuerungssysteme mit Python.
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