Catherine D. Schuman and J. Douglas Birdwell

November, 2013

PLOS ONE, Volume 8 (11).

http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0080455

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Abstract

Artificial neural networks (ANNs) are processors that are trained to perform particular tasks. We couple a computational ANN with a simulated affective system in order to explore the interaction between the two. In particular, we design a simple affective system that adjusts the threshold values in the neurons of our ANN. The aim of this paper is to demonstrate that this simple affective system can control the firing rate of the ensemble of neurons in the ANN, as well as to explore the coupling between the affective system and the processes of long term potentiation (LTP) and long term depression (LTD), and the effect of the parameters of the affective system on its performance. We apply our networks with affective systems to a simple pole balancing example and briefly discuss the effect of affective systems on network performance.

Citation Information

Text

author    C. D. Schuman and J. D. Birdwell
title     Dynamic Artificial Neural Networks with Affective Systems
journal   PLoS ONE
volume    8
number    11
month     November
year      2013
pages     e80455
publisher Public Library of Science
doi       10.1371/journal.pone.0080455

Bibtex

@ARTICLE{sb:13:dan,
  author = "C. D. Schuman and J. D. Birdwell",
  title = "Dynamic Artificial Neural Networks with Affective Systems",
  journal = "PLoS ONE",
  volume = "8",
  number = "11",
  month = "November",
  year = "2013",
  pages = "e80455",
  publisher = "Public Library of Science",
  doi = "10.1371/journal.pone.0080455",
  where = "http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0080455"
}