Name: Human–Robot Interaction Control Using Reinforcement Learning (Ieee Press Series on Systems Science and Engineering)
SKU: 53331649
Price: 4666.00 TWD
Availability: InStock
Author: Yu, Wen ; Perrusquia, Adolfo
ISBN: 9781119782742

portada Human–Robot Interaction Control Using Reinforcement Learning (Ieee Press Series on Systems Science and Engineering)

Human–Robot Interaction Control Using Reinforcement Learning (Ieee Press Series on Systems Science and Engineering)

Type

Physical Book

Author

Wen Yu

Adolfo Perrusquia

Publisher

Wiley-IEEE Press

Year

2021

Language

English

Pages

260

Format

Hardcover

Dimensions

22.9x15.2x1.8 cm

Weight

0.56 kg.

ISBN13

9781119782742

Edition No.

Synopsis "Human–Robot Interaction Control Using Reinforcement Learning (Ieee Press Series on Systems Science and Engineering) "

A comprehensive exploration of the control schemes of human-robot interactions In Human-Robot Interaction Control Using Reinforcement Learning, an expert team of authors delivers a concise overview of human-robot interaction control schemes and insightful presentations of novel, model-free and reinforcement learning controllers. The book begins with a brief introduction to state-of-the-art human-robot interaction control and reinforcement learning before moving on to describe the typical environment model. The authors also describe some of the most famous identification techniques for parameter estimation. Human-Robot Interaction Control Using Reinforcement Learning offers rigorous mathematical treatments and demonstrations that facilitate the understanding of control schemes and algorithms. It also describes stability and convergence analysis of human-robot interaction control and reinforcement learning based control. The authors also discuss advanced and cutting-edge topics, like inverse and velocity kinematics solutions, H2 neural control, and likely upcoming developments in the field of robotics. Readers will also enjoy: A thorough introduction to model-based human-robot interaction control Comprehensive explorations of model-free human-robot interaction control and human-in-the-loop control using Euler angles Practical discussions of reinforcement learning for robot position and force control, as well as continuous time reinforcement learning for robot force control In-depth examinations of robot control in worst-case uncertainty using reinforcement learning and the control of redundant robots using multi-agent reinforcement learning Perfect for senior undergraduate and graduate students, academic researchers, and industrial practitioners studying and working in the fields of robotics, learning control systems, neural networks, and computational intelligence, Human-Robot Interaction Control Using Reinforcement Learning is also an indispensable resource for students and professionals studying reinforcement learning.

Customers reviews

Have you read this book? Login to add your review.

More customer reviews

0% (0)
0% (0)
0% (0)
0% (0)
0% (0)

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

Human–Robot Interaction Control Using Reinforcement Learning (Ieee Press Series on Systems Science and Engineering) - Yu, Wen ; Perrusquia, Adolfo

Synopsis "Human–Robot Interaction Control Using Reinforcement Learning (Ieee Press Series on Systems Science and Engineering) "

Customers reviews

Frequently Asked Questions about the Book

Is the book original?

In what language is the book written?

What is the format of this book?

Questions and Answers about the Book

Opinions about Bookdelivery