Reinforcement Learning: An Introduction by Sutton & Barto

Dive into the foundational principles of reinforcement learning with this comprehensive guide by Richard S. Sutton and Andrew G. Barto. This essential textbook covers core concepts including Markov decision processes, temporal-difference learning, and policy gradient methods. Perfect for students, researchers, and practitioners seeking to understand how agents learn through interaction with their environment. Whether you're exploring machine learning for the first time or deepening your expertise, this book provides clear explanations, practical algorithms, and real-world applications. A must-have resource for anyone serious about artificial intelligence and autonomous systems.