Reward and Learn. Practical Reinforcement Learning for Autonomous Agents, Games, and Robot Control (en Inglés) - RICHARD BOOZMAN

Some systems are programmed.
Others learn.

Reinforcement learning enables machines to make decisions, learn from experience, and improve through feedback. It powers everything from game playing AI to robotics and autonomous control.

"Reward and Learn" is a practical, hands on guide to building reinforcement learning systems using Python and modern ML frameworks such as PyTorch.

This book focuses on real implementation, helping you move from theory to working intelligent agents.

Reinforcement learning is the foundation of decision making AI.

With the right approach, you can build systems that:

This book shows you how to build these systems step by step.

Throughout the book, you will learn how to:

Each chapter is designed to produce working results.

These examples reflect real world applications of RL.

If you want to build systems that learn from experience and adapt intelligently, this book provides the roadmap.

Learn from feedback.
Optimize decisions.
Build intelligent agents.