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

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

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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