Unlock The Secrets Of Neural Networks For Control Assembled By Paul J. Werbos Provided As Publication Copy

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,

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, TsaiHong Hong, Charles W, Anderson, W. Thomas Miller, III.