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 Title: Distributional Reinforcement Learning
 Author(s) Marc G. Bellemare, Will Dabney, Mark Rowland
 Publisher: The MIT Press (May 30, 2023); eBook (Creative Commons Licensed)
 License(s): CC BYNCND 2.0
 Hardcover: 384 pages
 eBook: PDF (385 pages) and PDF Files
 Language: English
 ISBN10: 0262048019
 ISBN13: 9780262048019
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Book Description
The first comprehensive guide to distributional reinforcement learning, providing a new mathematical formalism for thinking about decisions from a probabilistic perspective.
Distributional reinforcement learning is a new mathematical formalism for thinking about decisions. Going beyond the common approach to reinforcement learning and expected values, it focuses on the total reward or return obtained as a consequence of an agent's choicesâ€”specifically, how this return behaves from a probabilistic perspective.
About the Authors Marc G. Bellemare is Senior Staff Research Scientist, Google Research and Adjunct Professor, McGill University. Will Dabney is Senior Staff Research Scientist, DeepMind. Mark Rowland is Senior Research Scientist, DeepMind.
 Machine Learning
 Neural Networks and Depp Learning
 Artificial Intelligence
 Statistics, Mathematical Statistics, and SAS Programming
 Probability and Stochastic Processe
 Distributional Reinforcement Learning (Marc G. Bellemare, et al)
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