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  1. Bog
  2. Anvendt matematik
  3. Matematisk modellering

Control Systems and Reinforcement Learning

Af: Sean Meyn Engelsk Hardback

Control Systems and Reinforcement Learning

Af: Sean Meyn Engelsk Hardback
Tjek vores konkurrenters priser
A high school student can create deep Q-learning code to control her robot, without any understanding of the meaning of ''deep'' or ''Q'', or why the code sometimes fails. This book is designed to explain the science behind reinforcement learning and optimal control in a way that is accessible to students with a background in calculus and matrix algebra. A unique focus is algorithm design to obtain the fastest possible speed of convergence for learning algorithms, along with insight into why reinforcement learning sometimes fails. Advanced stochastic process theory is avoided at the start by substituting random exploration with more intuitive deterministic probing for learning. Once these ideas are understood, it is not difficult to master techniques rooted in stochastic control. These topics are covered in the second part of the book, starting with Markov chain theory and ending with a fresh look at actor-critic methods for reinforcement learning.
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Tjek vores konkurrenters priser
A high school student can create deep Q-learning code to control her robot, without any understanding of the meaning of ''deep'' or ''Q'', or why the code sometimes fails. This book is designed to explain the science behind reinforcement learning and optimal control in a way that is accessible to students with a background in calculus and matrix algebra. A unique focus is algorithm design to obtain the fastest possible speed of convergence for learning algorithms, along with insight into why reinforcement learning sometimes fails. Advanced stochastic process theory is avoided at the start by substituting random exploration with more intuitive deterministic probing for learning. Once these ideas are understood, it is not difficult to master techniques rooted in stochastic control. These topics are covered in the second part of the book, starting with Markov chain theory and ending with a fresh look at actor-critic methods for reinforcement learning.
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Se mere i:
Produktdetaljer
Sprog: Engelsk
Sider: 450
ISBN-13: 9781316511961
Indbinding: Hardback
Udgave:
ISBN-10: 1316511960
Kategori: Matematisk modellering
Udg. Dato: 9 jun 2022
Længde: 28mm
Bredde: 262mm
Højde: 183mm
Forlag: Cambridge University Press
Oplagsdato: 9 jun 2022
Forfatter(e): Sean Meyn
Forfatter(e) Sean Meyn

Kategori Matematisk modellering

ISBN-13 9781316511961

Sprog Engelsk

Indbinding Hardback

Sider 450

Udgave

Længde 28mm

Bredde 262mm

Højde 183mm

Udg. Dato 9 jun 2022

Oplagsdato 9 jun 2022

Forlag Cambridge University Press

Kategori sammenhænge