Next Article in Journal
Symbolic Computation of Recursion Operators for Nonlinear Differential-Difference Equations
Previous Article in Journal
Numerical Study of Collision Efficiency of Dust Particles
Article Menu

Article Versions

Export Article

Open AccessArticle
Math. Comput. Appl. 1999, 4(3), 305-314; doi:10.3390/mca4030305

Building Evolution Friendliness into Cellular Automation Dynamics: The Cytomatrix Neuron Model

Department of Computer Science, Wayne State University Detroit, MI 48202, USA
*
Author to whom correspondence should be addressed.
Published: 1 December 1999
Download PDF [4717 KB, uploaded 5 April 2016]

Abstract

The cytomatrix neuron is a softened cellular automaton, roughly motivated by interactions that could occur in a molecular or cellular complex. Subcells exert graded influences on each other and provide a medium for the integration of input signals in space and time. A readout element located in a suitably activated subcell triggers an output. The neurons are trained through variation-selection learning that acts on multiple dynamical parameters. Extensive experimentation with the model shows that the dynamics can be molded to yield different structures of generalization. Dimensionality can be increased by increasing the number of dynamical parameters open to variation and selection. Learning algorithms that vary the greatest number of parameters were found to have a greater variability in the structures of generalization and to yield higher performance values and learning rates. The focus here is on n-bit exclusive- OR tasks that are known to be hard due to their linear inseparability. The system successfully learned 2-bit and 4-bit exclusive-OR functions. The higher dimensional algorithms exhibited a relatively good performance on the 8-bit exclusive-OR function.
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Ugur, A.; Conrad, M. Building Evolution Friendliness into Cellular Automation Dynamics: The Cytomatrix Neuron Model. Math. Comput. Appl. 1999, 4, 305-314.

Show more citation formats Show less citations formats

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Math. Comput. Appl. EISSN 2297-8747 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top