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Books like Reinforcement learning by Richard S. Sutton


Reinforcement learning is a computational framework in which an agent learns to maximize cumulative reward by interacting with its environment. This book outlines the fundamental concepts and algorithms of reinforcement learning. Part I formalizes the problem using Markov decision processes. Part II explores basic solution methods—including dynamic programming, Monte Carlo approaches, and temporal‑difference learning. Part III integrates these methods with artificial neural networks, eligibility traces, and planning, and concludes with practical case studies and a discussion of future directions.
First publish date: 1998
Genre: Technology & Computing/Artificial Intelligence
Authors: Richard S. Sutton
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Reinforcement learning by Richard S. Sutton

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Books similar to Reinforcement learning (8 similar books)

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Some Other Similar Books

Machine Learning: A Probabilistic Perspective by Kevin P. Murphy
Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto
Deep Reinforcement Learning by Y. Zhang, R. Zhang
Artificial Intelligence: A Modern Approach by Stuart Russell, Peter Norvig
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