Hallo! Tracked shipping to Netherlands with Delivery Duty Paid for just €7 

Ship to
Netherlands
0

My Account

  • argentina
  • chile
  • colombia
  • españa
  • méxico
  • perú
  • estados unidos
  • internacional

menu

Select your country

Americas

Europe

Rest of the world

portada Distributional Reinforcement Learning (Adaptive Computation and Machine Learning)
Type
Physical Book
Publisher
Author
Language
English
Pages
384
Format
Hardcover
ISBN13
9780262048019

Distributional Reinforcement Learning (Adaptive Computation and Machine Learning)

Marc G. Bellemare; Will Dabney; Mark Rowland (Author) · The Mit Press · Hardcover

Distributional Reinforcement Learning (Adaptive Computation and Machine Learning) - Marc G. Bellemare; Will Dabney; Mark Rowland

Cheaper New Book Imported to Netherlands
Delivery: 10 Sep - 14 Sep Shipping: 18 to 19 business days.
€ 44,93
Faster New Book Imported to Netherlands
Delivery: 18 Aug - 19 Aug Shipping: 2 to 2 business days.
€ 74,15
Import costs and 9% BTW included in the price ✅
€ 44,93

Choose the list to add your product or create one New List

Go to My Wishlists
Calculate shipping cost

Synopsis "Distributional Reinforcement Learning (Adaptive Computation and Machine Learning) "

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. In this first comprehensive guide to distributional reinforcement learning, Marc G. Bellemare, Will Dabney, and Mark Rowland, who spearheaded development of the field, present its key concepts and review some of its many applications. They demonstrate its power to account for many complex, interesting phenomena that arise from interactions with one's environment. The authors present core ideas from classical reinforcement learning to contextualize distributional topics and include mathematical proofs pertaining to major results discussed in the text. They guide the reader through a series of algorithmic and mathematical developments that, in turn, characterize, compute, estimate, and make decisions on the basis of the random return. Practitioners in disciplines as diverse as finance (risk management), computational neuroscience, computational psychiatry, psychology, macroeconomics, and robotics are already using distributional reinforcement learning, paving the way for its expanding applications in mathematical finance, engineering, and the life sciences. More than a mathematical approach, distributional reinforcement learning represents a new perspective on how intelligent agents make predictions and decisions.

Customers reviews

More customer reviews
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)

Frequently Asked Questions about the Book

Is the book original?

All books in our catalog are Original.

In what language is the book written?

The book is written in English.

What is the format of this book?

The binding of this edition is Hardcover.

Questions and Answers about the Book

Do you have a question about the book? Login to be able to add your own question.

Opinions about Bookdelivery

More customer reviews