Reinforcement Learning, second edition: An Introduction Hardcover-image
Reinforcement Learning, second edition: An Introduction Hardcover-image

Reinforcement Learning, second edition: An Introduction Hardcover

$ 26.4

Subject: Programming / Algorithms, Intelligence (Ai) & Semantics, Neural Networks Series: Adaptive Computation and Machine Learning Ser. Country of Origin: United States Format: Hardcover Item Height: 1.5 in Publisher: MIT Press Item Weight: 41.6 Oz ISBN: 9780262039246 Language: English Item Width: 7.3 in Publication Year: 2018 Subject Area: Computers Publication Name: Reinforcement Learning, second edition: An Introduction Hardcover Author: Richard S. Sutton, Andrew G. Barto width: 7.3 in Type: Textbook height: 1.5 in Item Length: 11.2 in

Description

Reinforcement Learning, second edition: An Introduction Hardcover. "Reinforcement Learning, second edition: An Introduction Hardcover" is a comprehensive textbook written by Richard S. Sutton and Andrew G. Barto, published by MIT Press in 2018. This second edition book delves into the subject area of reinforcement learning, focusing on computer programming, algorithms, neural networks, and artificial intelligence. With detailed explanations and insights, it serves as a valuable resource for students and professionals alike who want to deepen their understanding of this advanced field. The hardcover format makes it a sturdy and durable reference book for those studying or working in the realm of reinforcement learning. "Reinforcement Learning, second edition: An Introduction Hardcover" is a comprehensive textbook written by Richard S. Sutton and Andrew G. Barto, published by MIT Press in 2018. This second edition book delves into the subject area of reinforcement learning, focusing on computer programming, algorithms, neural networks, and artificial intelligence. With detailed explanations and insights, it serves as a valuable resource for students and professionals alike who want to deepen their understanding of this advanced field. The hardcover format makes it a sturdy and durable reference book for those studying or working in the realm of reinforcement learning.

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