Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Hands-On Reinforcement Learning for Autonomous AI Agents: Practical Python Techniques for Real-World Solutions

Hands-On Reinforcement Learning for Autonomous AI Agents: Practical Python Techniques for Real-World Solutions

Tyson, Ethan

Paperback

Series: The Robust Agent, Book 4

Technology & Engineering

ISBN13: 9798293161522
Publisher: Independently Published
Published: Jul 19 2025
Pages: 142
Weight: 0.57
Height: 0.30 Width: 7.00 Depth: 10.00
Language: English
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)

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