Sadece Litres-də oxuyun

Kitab fayl olaraq yüklənə bilməz, yalnız mobil tətbiq və ya onlayn olaraq veb saytımızda oxuna bilər.

0+
mətn
PDF

Həcm 289 səhifələri

0+

Human-Robot Interaction Control Using Reinforcement Learning

mətn
PDF
Sadece Litres-də oxuyun

Kitab fayl olaraq yüklənə bilməz, yalnız mobil tətbiq və ya onlayn olaraq veb saytımızda oxuna bilər.

260,81 ₼
10% endirim hədiyyə edin
Bu kitabı tövsiyə edin və dostunuzun alışından 26,09 ₼ əldə edin.

Kitab haqqında

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.

Janr və etiketlər

Rəy bildirmək

Giriş, kitabı qiymətləndirmək və rəy bildirmək

Kitabın təsviri

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.

Kitab Wen Yu, Adolfo Perrusquia «Human-Robot Interaction Control Using Reinforcement Learning» — saytda onlayn oxuyun. Şərh və rəylərinizi qeyd edin, sevimlilərinizi seçin.
Yaş həddi:
0+
Həcm:
289 səh.
ISBN:
9781119782759
Ümumi ölçü:
26 МБ
Səhifələrin ümumi sayı:
289
Naşir:
Müəllif hüququ sahibi:
John Wiley & Sons Limited