Hands-On Reinforcement Learning for Autonomous AI Agents (Paperback). Dieser Artikel ist nicht verfügbar.

Sprache: Englisch

Verlag: Independently Published, 2025

9798293161522

Serie: Buch 4 von 5 - The Robust Agent Series

Anbieter: Grand Eagle Retail, Bensenville, IL, USAGrand Eagle Retail

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Verkäufer:in bei AbeBooks seit 12. Oktober 2005

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Zustand: Neu

EUR 20,70

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Artikelbeschreibung des Verkäufers

Paperback. Hands-On Reinforcement Learning for Autonomous AI Agents: Practical Python Techniques for Real-World Solutions Are you ready to transform your ideas into intelligent, self-learning systems that solve real-world problems? **Hands-On Reinforcement Learning for Autonomous AI Agents** delivers the practical Python techniques you need to build, train, and deploy agents that adapt and excel in dynamic environments. This book shows you how to master reinforcement learning from the ground up. You'll explore foundational methods-like tabular Q-Learning and Deep Q-Networks-before advancing to policy-based algorithms such as PPO, A2C, and SAC. You'll discover how to leverage cutting-edge architectures like Dreamer's world models and Decision Transformers, and orchestrate multi-agent ecosystems with PettingZoo and Ray RLlib. Every chapter is packed with real-world code examples, detailed explanations, and hands-on projects-from traffic signal control to warehouse robotics and beyond. What you'll gain: * Proficiency in Python-powered RL frameworks (Gymnasium, Stable Baselines3, PyTorch)* Ability to implement, tune, and evaluate agents for tasks ranging from discrete games to continuous control* Expertise in safe exploration, reward shaping, and preventing reward hacking in complex environments* Strategies for scalable deployment: Docker containers, Kubernetes orchestration, and edge inference with ONNX and quantized models* Skills in interpreting agent behavior using SHAP, saliency maps, and human-in-the-loop feedback pipelines Whether you're an AI engineer, robotics developer, or data scientist, this book empowers you to build robust, interpretable, and production-ready autonomous agents. Turn theoretical concepts into working solutions that drive efficiency and innovation across industries. Ready to take control of your next reinforcement learning project? Add **Hands-On Reinforcement Learning for Autonomous AI Agents** to your toolkit today and start creating intelligent systems that learn, adapt, and deliver real-world impact. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

Bestandsnummer des Verkäufers 9798293161522

Titel
Hands-On Reinforcement Learning for Autonomous AI Agents (Paperback)
Autor
Ethan Tyson
Verlag
Independently Published
Erscheinungsjahr
2025
Zustand
new
Einband
Paperback
Sprache
Englisch
ISBN-13
9798293161522
Serie
Buch 4 von 5: The Robust Agent Series

Suchergebnisse für Hands-On Reinforcement Learning for Autonomous AI Agents (Paperback)