Reinforcement learning (RL) will deliver one of the biggest
breakthroughs in AI over the next decade, enabling algorithms to
learn from their environment to achieve arbitrary goals. This
exciting development avoids constraints found in traditional
machine learning (ML) algorithms. This practical book shows data
science and AI professionals how to learn by reinforcement and
enable a machine to learn by itself. Author Phil Winder of Winder
Research covers everything from basic building blocks to
state-of-the-art practices. You'll explore the current state of RL,
focus on industrial applications, learn numerous algorithms, and
benefit from dedicated chapters on deploying RL solutions to
production. This is no cookbook; doesn't shy away from math and
expects familiarity with ML. Learn what RL is and how the
algorithms help solve problems Become grounded in RL fundamentals
including Markov decision processes, dynamic programming, and
temporal difference learning Dive deep into a range of value and
policy gradient methods Apply advanced RL solutions such as meta
learning, hierarchical learning, multi-agent, and imitation
learning Understand cutting-edge deep RL algorithms including
Rainbow, PPO, TD3, SAC, and more Get practical examples through the
accompanying website
General
Imprint: |
O'Reilly Media
|
Country of origin: |
United States |
Release date: |
November 2020 |
Authors: |
Phil Winder Ph.D.
|
Dimensions: |
233 x 178 x 26mm (L x W x T) |
Format: |
Paperback
|
Pages: |
350 |
ISBN-13: |
978-1-09-811483-1 |
Categories: |
Books
|
LSN: |
1-09-811483-3 |
Barcode: |
9781098114831 |
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