Neural Networks for Control

摘要:

Neural Networks for Control highlights key issues in learning control and identifiesresearch directions that could lead to practical solutions for control problems in criticalapplication domains. It addresses general issues of neural network based control and neural networklearning with regard to specific problems of motion planning and control in robotics, and takes upapplication domains well suited to the capabilities of neural network controllers. The appendixdescribes seven benchmark control problems.W. Thomas Miller, III is Professor of Electrical andComputer Engineering at the University of New Hampshire. Richard S. Sutton works for GTELaboratories Incorporated. Paul J. Werbos is Program Director for Neuroengineering at the NationalScience 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. CharlesC. Jorgensen, C. Schley. Martin Herman, James S. Albus, Tsai-Hong Hong. Charles W. Anderson, W.Thomas Miller, III.