Student work
Self-organization
Populations
Artificial life
Ecology
Software
Links
Contact
Home
Sorting and Template

Please note

The simulation needs a Java-Plugin (1.3.x) installed for your internet browser. If you do not already have one installed, the browser will prompt you to download the Plugin from “Sun”, who is the inventor of Java. Please download the JRE (=Java runtime environment) into a directory on your computer (e.g. “c:\temp”), execute the downloaded file for installation on your system (double-click on the file). Afterwards you will be able to reload the simulation page. Maybe you will have to restart your browser to succeed.

Run the simulation

Please click here.

Description of the simulation

This simulation is based on the simulation “sorting performed by ants”. We additionally implemented an environmental template in this simulation.

Ants collectively sort their brood in spatially different areas. They discriminate between different stages of the brood, which need different incubation temperatures in their local environment. As the diurnal rhythm of the temperature gradient in the soil changes this local temperature, the ants collectively shift the brood upwards or downwards in the soil. This way, the brood is always incubated at the adequate temperature.

Image taken from: Bonabeau E., Dorigo M. and Theraulaz G. (1999) Swarm intelligence. From natural to artificial systems. Santa Fee Institute studies in the sciences of complexity. Oxford University Press

To simulate this behavior, we introduced an environmental template with 3 concentric circles, each causing a slight preferential drop-rate of similar colored pieces.

Parameters

The slider density-of-chips sets the density of chips distributed randomly at the beginning

The slider number sets the number of ants that are used in the simulation

The sliders Puturn and turn-angle set the basic parameters of the random walk. Please note that the ants always perform simply a random walk.

The slider alpha sets the value of the parameter used in the first equation. It simply scales the interpretation of “similarity”.

The button show-template displays the template for 5 seconds and then automatically returns to the simulation view. NOTE: Never press this button while the simulation is running. Stop the simulation before!

Experiments

  • Check how the number of actors and of the chip density affect the sorting speed and result.
  • Study the importance of “alpha”.

Screenshot

This picture shows the initial distribution of chips:

This series of picture shows, how the pattern evolves:

Implementation

The presented NetLogo simulation was written by:
Thomas Schmickl (2002), Department for Zoology, Karl-Franzens-University Graz, Austria, Europe,
schmickl@nextra.at, thomas.schmickl@uni-graz.at

Further readings

  • Camazine S., Deneubourg J.-L., Franks N.R., Sneyd J., Theraulaz G. and Bonabeau E. (2001) Self-Organization in biological systems. Princeton University Press
  • Resnick M. (2000) Turtles, termites and traffic jams. MIT Press.
  • Bonabeau E., Dorigo M. and Theraulaz G. (1999) Swarm intelligence. From natural to artificial systems. Santa Fee Institute studies in the sciences of complexity. Oxford University Press.

[Home] [Self-organization] [Ecology] [Populations] [Artificial life] [Student work] [Software] [Links] [Contact]