Princeton University Press / Neural Networks / Academic Press Inc. / MIT Press / Actor-Critic Elman Networks / Dynamic Recurrent Neural Networks / Hertz / /
Country
Japan / Jordan / Australia / / /
Facility
Prentice Hall / University of New South Wales / University of Rochester / Operations Research University of California / Massachusetts Institute of Technology / /
University of New South Wales / Sydney / World Congress / Machine Intelligence / School of Computer Science and Engineering / Learning and Machine Intelligence / Princeton University / University of California / Berkeley / Operations Research University / Massachusetts Institute of Technology / University of Rochester / U.S. Securities and Exchange Commission / Computational Intelligence / Eiji Mizutani Stuart E. Dreyfus Department of Computer Science Tsing Hua University Hsinchu / /
Person
John N. Tsitsiklis / Andrew G. Barto / Hence / Long-Ji Lin / Richard S. Sutton / Stuart E. Dreyfus / Paul J. Werbos / Fernando Mark Pendrith / Eiji Mizutani / Steven D. Whitehead / Dimtri P. Bertsekas / Averill M. Law / Barak A. Pearlmutter / Eiji Mizutani Stuart / /
Position
baseball outfielder / Actor / Critic and Actor / Critic / /
Two stochastic dynamic programming problems by model-free actor-critic recurrent-network learning in non-Markovian settings Eiji Mizutani Stuart E. Dreyfus