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题名/责任者:

Model-based reinforcement learning : from data to continuous actions with a Python-based toolbox / Milad Farsi (University of Waterloo), Jun Liu (University of Waterloo).

出版发行项:

Hoboken, New Jersey : Wiley, [2023]

ISBN:

9781119808572

ISBN:

111980857X

载体形态项:

xxxv, 226 pages : illustrations ; 24 cm.

其他载体形态:

Online version: Farsi, Milad. Model-based reinforcement learning Hoboken, New Jersey : Wiley, [2023] 9781119808589

丛编说明:

Wiley-IEEE press book series on control systems theory and applications

个人责任者:

Farsi, Milad, author.

附加个人名称:

Liu, Jun (Professor of applied mathematics), author.

论题主题:

Reinforcement learning.

论题主题:

Reinforcement learning-Mathematical models.

中图法分类号:

TP181

书目附注:

Includes bibliographical references and index.

摘要附注:

"Whilst reinforcement learning has gained tremendous success and popularity in recent years, most research papers and books focus on either the theory (optimal control and dynamic programming) or the algorithms (mostly simulation-based). From a control systems perspective, this book will provide a model-based framework that bridges these two aspects to provide a holistic treatment of the topic of model-based online learning control. The aim is to develop a model-based framework for data-driven control that encompasses the topics of systems identification from data, model-based reinforcement learning and optimal control, and their applications. This will be done through reviewing the classical results in system identification from a new perspective to develop more efficient reinforcement learning techniques. Hence, the focus of this book will be on presenting an end to end framework from design to application of a more tractable model-based reinforcement learning technique. The tutorial aspects of the book are enhanced by the provision of a Python-based toolbox, accessible online"--

豆瓣简介：