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Distributional Reinforcement Learning
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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 BY-NC-ND 2.0
  • Hardcover: 384 pages
  • eBook: PDF (385 pages) and PDF Files
  • Language: English
  • ISBN-10: 0262048019
  • ISBN-13: 978-0262048019
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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 choices—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.
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