Neural Network Implementation of Admission Control
Abstract
A feedforward layered network implements a mapping required to control an unknown stochastic nonlinear dynamical system. Training is based on a novel approach that combines stochastic approximation ideas with back(cid:173) propagation. The method is applied to control admission into a queueing sys(cid:173) tem operating in a time-varying environment.
Cite
Text
Milito et al. "Neural Network Implementation of Admission Control." Neural Information Processing Systems, 1990.Markdown
[Milito et al. "Neural Network Implementation of Admission Control." Neural Information Processing Systems, 1990.](https://mlanthology.org/neurips/1990/milito1990neurips-neural/)BibTeX
@inproceedings{milito1990neurips-neural,
title = {{Neural Network Implementation of Admission Control}},
author = {Milito, Rodolfo A. and Guyon, Isabelle and Solla, Sara A.},
booktitle = {Neural Information Processing Systems},
year = {1990},
pages = {493-499},
url = {https://mlanthology.org/neurips/1990/milito1990neurips-neural/}
}