Can I read Human-Robot Interaction Control Using Reinforcement Learning (IEEE Press Series on Systems Science and Engineering) on EtoBox?

Human-Robot Interaction Control Using Reinforcement Learning (IEEE Press Series on Systems Science and Engineering) by Wen Yu, Adolfo Perrusquia is a nonfiction available to read on EtoBox.

What is Human-Robot Interaction Control Using Reinforcement Learning (IEEE Press Series on Systems Science and Engineering) about?

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 int

Who reads Human-Robot Interaction Control Using Reinforcement Learning (IEEE Press Series on Systems Science and Engineering)?

Author

Wen Yu, Adolfo Perrusquia

Publisher

Wiley-IEEE Press

Published

2021

Language

EN

ISBN

9781119782766

Category

nonfiction

Subjects

Engineering, Science, Computer Science