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

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