Neural Networks for Control highlights key issues in learning control and identifies research directions that could lead to practical solutions for control problems in critical application domains. It addresses general issues of neural network based control and neural network learning with regard to specific problems of motion planning and control in robotics, and takes up application domains well suited to the capabilities of neural network controllers. The appendix describes seven benchmark control problems.W. Thomas Miller, III is Professor of Electrical and Computer Engineering at the University of New Hampshire. Richard S. Sutton works for GTE Laboratories Incorporated. Paul J. Werbos is Program Director for Neuroengineering at the National Science Foundation.Contributors: Andrew G. Barto. Ronald J. Williams. Paul J. Werbos. Kumpati S. Narendra. L. Gordon Kraft, III, David P. Campagna. Mitsuo Kawato. Bartlett W. Met. Christopher G. Atkeson, David J. Reinkensmeyer. Derrick Nguyen, Bernard Widrow. James C. Houk, Satinder P. Singh, Charles Fisher. Judy A. Franklin, Oliver G. Selfridge. Arthur C. Sanderson. Lyle H. Ungar. Charles C. Jorgensen, C. Schley. Martin Herman, James S. Albus, Tsai-Hong Hong. Charles W. Anderson, W. Thomas Miller, III.
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Book Description
Editorial Reviews
Review
"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
About the Author
W. Thomas Miller III is Professor and Chairman of Electrical and Computer Engineering at the University of New Hampshire. Richard S. Sutton works for GTE Laboratories Incorporated. Paul J. Werbos is Program Director for Neuroengineering at the National Science Foundation.
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2 of 3 people found the following review helpful:
1.0 out of 5 stars
A book for specialists,
By Matteo Gadioli (USA) - See all my reviews
This review is from: Neural Networks for Control (Paperback)
More than a book it is a collection of papers, not always easy to understand and written in academic language. It could be used as a reference by one who knows already the subject. Not recommended for beginners
2 of 5 people found the following review helpful:
1.0 out of 5 stars
A book for specialists,
By Matteo Gadioli (USA) - See all my reviews
This review is from: Neural Networks for Control (Paperback)
More than a book it is a collection of papers, not always easy to understand and written in academic language. It could be used as a reference by one who knows already the subject. Not recommended for beginners
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Figure 1.1 is a sketch of my mental model of the recent history of connectionist research in relation to engineering and artificial intelligence (AI). Read the first page Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, General Principles, Biological Cybernetics, Planner Manager, University of Massachusetts, San Diego, Morgan Kaufmann, Academic Press, Englewood Cliffs, American Control Conference, Homem de Mello, San Mateo, Control Systems Magazine, University of California, University of New Hampshire, Cambridge University, Department of Computer Science, Department of Electrical Engineering, International Journal of Robotics Research, International Symposium, Interval Input, Journal of Dynamic Systems, Journal of Physiology, National Science Foundation, New Haven New!
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Figure 1.1 is a sketch of my mental model of the recent history of connectionist research in relation to engineering and artificial intelligence (AI). Read the first page Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, General Principles, Biological Cybernetics, Planner Manager, University of Massachusetts, San Diego, Morgan Kaufmann, Academic Press, Englewood Cliffs, American Control Conference, Homem de Mello, San Mateo, Control Systems Magazine, University of California, University of New Hampshire, Cambridge University, Department of Computer Science, Department of Electrical Engineering, International Journal of Robotics Research, International Symposium, Interval Input, Journal of Dynamic Systems, Journal of Physiology, National Science Foundation, New Haven New!
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 28
books:
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100
books
cite this book:
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- Adaptive Control (Communications and Control Engineering) by Rogelio Lozano on page 169, page 350, and page 509
- The Connection Machine (Mit Press Series in Artificial Intelligence) by W. Daniel Hillis on page 255, page 257, and page 282
- Reinforcement Learning (The Springer International Series in Engineering and Computer Science) by Richard S. Sutton on page 44, and page 70
- Cognitive Science (Handbook of Perception and Cognition, Second Edition) by Benjamin Martin Bly on page 114, and page 251
- Automatic Flight Control, Fourth Edition by E. H. J. Pallett on page 404, and page 485
See all 28 books this book cites
- Advances In Intelligent Control (Series in Systems and Control) by C J Harris on 6 pages
- Neural Network Control of Nonlinear Discrete-Time Systems (Automation and Control Engineering) by Jagannathan Sarangapani on 6 pages
- Neural Systems for Robotics by Omid Omidvar on 4 pages
- Neural Network Control Of Robot Manipulators And Non-Linear Systems (Series in Systems and Control) by F W Lewis on 4 pages
- Fuzzy and Neural Approaches in Engineering (Adaptive and Learning Systems for Signal Processing, Communications and Control Series) by Lefteri H. Tsoukalas on 4 pages
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