IJCNN '93 - Nagoya: Proceedings of 1993 International Joint Conference on Neural Networks, Nagoya Congress Center, October 25-29, 1993, Japan, Volume 2 |
Contents
VOL 1 | 1076 |
University of Bari | 1082 |
A Reinforcement Learning | 1083 |
Copyright | |
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adaptive applied approach approximation architecture Artificial Neural Networks back-propagation binary cells classification coefficient complex computation connection constraint control system convergence corresponding cortex defined denotes dynamics equation error example feedback feedforward Figure global graph Hamming distance hidden layer hidden units Hopfield Hopfield network IEEE implemented initial input layer input pattern input vector internal iteration Japan learning algorithm linear local minima mapping matrix memory method minimization modules netel neural net neurons node noise nonlinear number of hidden object obtained optimization problems output layer output units paper parallel Parallel Distributed Processing parameters pattern recognition perceptron performance pixels Proc propagation proposed random receptive field representation represented robot sample sensory shown in Fig shows sigmoid sigmoid function signal simulated annealing solution space structure supervised learning task theorem threshold tion traveling salesman problem update variables visual weights