Next Article in Journal
Mapping Ground Instability in Areas of Geotechnical Infrastructure Using Satellite InSAR and Small UAV Surveying: A Case Study in Northern Ireland
Previous Article in Journal
Desertification Assessment Using MEDALUS Model in Watershed Oued El Maleh, Morocco
Article Menu
Issue 3 (September) cover image

Export Article

Open AccessArticle
Geosciences 2017, 7(3), 49; doi:10.3390/geosciences7030049

Evolution of Neural Dynamics in an Ecological Model

School of Informatics and Computing, Indiana University, 919 E. 10th St., Bloomington, IN 47408, USA
*
Author to whom correspondence should be addressed.
Received: 14 March 2017 / Revised: 20 June 2017 / Accepted: 27 June 2017 / Published: 4 July 2017
(This article belongs to the Special Issue Individual-Based Ecological Modeling)
View Full-Text   |   Download PDF [589 KB, uploaded 4 July 2017]   |  

Abstract

What is the optimal level of chaos in a computational system? If a system is too chaotic, it cannot reliably store information. If it is too ordered, it cannot transmit information. A variety of computational systems exhibit dynamics at the “edge of chaos”, the transition between the ordered and chaotic regimes. In this work, we examine the evolved neural networks of Polyworld, an artificial life model consisting of a simulated ecology populated with biologically inspired agents. As these agents adapt to their environment, their initially simple neural networks become increasingly capable of exhibiting rich dynamics. Dynamical systems analysis reveals that natural selection drives these networks toward the edge of chaos until the agent population is able to sustain itself. After this point, the evolutionary trend stabilizes, with neural dynamics remaining on average significantly far from the transition to chaos. View Full-Text
Keywords: agent-based modeling; artificial life; neural networks; evolution; chaos agent-based modeling; artificial life; neural networks; evolution; chaos
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary material

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

Williams, S.; Yaeger, L. Evolution of Neural Dynamics in an Ecological Model. Geosciences 2017, 7, 49.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Geosciences EISSN 2076-3263 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top