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How do robots learn to walk, balance, grasp objects, and move through unpredictable environments? The answer lies in reinforcement learning, a powerful branch of artificial intelligence that enables machines to improve their behavior through experience, feedback, and trial-and-error learning.
Reinforcement Learning in Robotics provides a practical introduction to how autonomous robots use learning algorithms to develop intelligent movement and decision-making abilities. From robotic locomotion and manipulation to navigation and real-world interaction, this book explains the principles behind training robots that can adapt, improve, and operate in complex environments.
Inside this book, you will discover:
Whether you are a robotics student, engineer, AI enthusiast, researcher, or developer exploring autonomous machines, this book offers a clear pathway into one of the most exciting areas of modern robotics.
By combining artificial intelligence with physical systems, reinforcement learning is transforming robots from programmed machines into adaptive learners. This book will help you understand the technologies shaping the next generation of intelligent robotic systems.
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