Richard S. Sutton Books
Sutton is a Canadian computer scientist known for his pioneering work in reinforcement learning and artificial intelligence.
Known for: Reinforcement Learning: An Introduction
Books by Richard S. Sutton
Reinforcement Learning: An Introduction
This foundational textbook provides a comprehensive introduction to reinforcement learning, a branch of machine learning concerned with how agents can learn to make decisions through interaction with their environment. It covers key concepts such as Markov decision processes, dynamic programming, Monte Carlo methods, temporal-difference learning, and policy gradient techniques. The book is widely used in academia and industry as a standard reference for understanding the theoretical and practical aspects of reinforcement learning.
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Formulating the Reinforcement Learning Problem with Markov Decision Processes
It always starts with the formulation. Every learning problem in reinforcement learning must be grounded in the interplay between the agent and the environment. This is captured neatly through the Markov Decision Process (MDP)—a mathematical model that binds states, actions, transitions, rewards, an...
From Reinforcement Learning: An Introduction
Dynamic Programming: Solving MDPs with Full Knowledge
Dynamic Programming (DP) is where reinforcement learning finds its computational heartbeat for problems with known models. When transitions and rewards are fully specified, we can exploit mathematical precision to compute optimal policies through iterative refinement. Policy evaluation calculates t...
From Reinforcement Learning: An Introduction
About Richard S. Sutton
Sutton is a Canadian computer scientist known for his pioneering work in reinforcement learning and artificial intelligence.
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Sutton is a Canadian computer scientist known for his pioneering work in reinforcement learning and artificial intelligence.
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