Overview

This work brings together examples of all the most important paradigms for the application of neural networks to robotics and control. Primarily concerned with engineering problems and approaches to their solution through neurocomputing systems, the book is divided into three sections: general principles; motion control; and applications domains (with evaluations of the possible applications by expertsin the applications areas). Special emphasis is placed on designs based on optimization or reinforcement, which will become increasingly important as researchers address more complex engineering challenges or real biological-control problems.

Full Product Details

9780262631617

Table of Contents

Reviews

Highly recommended. --Nick Beard, Computing A useful book for students and researchers alike, from any discipline that is interested in ANN-based controllers. --Judy A. Franklin, IEEE Transactions on Neural Networks

Highly recommended. Nick Beard, Computing A useful book for students and researchers alike, from any disciplinethat is interested in ANN-based controllers. Judy A. Franklin , IEEE Transactions on Neural Networks

Author Information

W. Thomas Miller, III is Professor of Electrical and Computer Engineering at the University of New Hampshire. Richard S. Sutton is Professor of Computing Science and AITF Chair in Reinforcement Learning and Artificial Intelligence at the University of Alberta, and also Distinguished Research Scientist at DeepMind. Paul J. Werbos is Program Director for Neuroengineering at the National Science Foundation.

Tab Content 6

Customer Reviews

Recent Reviews

Countries Available