Mixtures of Controllers for Jump Linear and Non-Linear Plants
Abstract
We describe an extension to the Mixture of Experts architecture for modelling and controlling dynamical systems which exhibit multi(cid:173) ple modes of behavior. This extension is based on a Markov process model, and suggests a recurrent network for gating a set of linear or non-linear controllers. The new architecture is demonstrated to be capable of learning effective control strategies for jump linear and non-linear plants with multiple modes of behavior.
Cite
Text
Cacciatore and Nowlan. "Mixtures of Controllers for Jump Linear and Non-Linear Plants." Neural Information Processing Systems, 1993.Markdown
[Cacciatore and Nowlan. "Mixtures of Controllers for Jump Linear and Non-Linear Plants." Neural Information Processing Systems, 1993.](https://mlanthology.org/neurips/1993/cacciatore1993neurips-mixtures/)BibTeX
@inproceedings{cacciatore1993neurips-mixtures,
title = {{Mixtures of Controllers for Jump Linear and Non-Linear Plants}},
author = {Cacciatore, Timothy W. and Nowlan, Steven J.},
booktitle = {Neural Information Processing Systems},
year = {1993},
pages = {719-726},
url = {https://mlanthology.org/neurips/1993/cacciatore1993neurips-mixtures/}
}