NetLogo Models Library:
In this project, a colony of ants forages for food. Though each ant follows a set of simple rules, the colony as a whole acts in a sophisticated way.
When an ant finds a piece of food, it carries the food back to the nest, dropping a chemical as it moves. When other ants "sniff" the chemical, they follow the chemical toward the food. As more ants carry food to the nest, they reinforce the chemical trail.
Click the SETUP button to set up the ant nest (in violet, at center) and three piles of food. Click the GO button to start the simulation. The chemical is shown in a green-to-white gradient.
The EVAPORATION-RATE slider controls the evaporation rate of the chemical. The DIFFUSION-RATE slider controls the diffusion rate of the chemical.
If you want to change the number of ants, move the POPULATION slider before pressing SETUP.
The ant colony generally exploits the food source in order, starting with the food closest to the nest, and finishing with the food most distant from the nest. It is more difficult for the ants to form a stable trail to the more distant food, since the chemical trail has more time to evaporate and diffuse before being reinforced.
Once the colony finishes collecting the closest food, the chemical trail to that food naturally disappears, freeing up ants to help collect the other food sources. The more distant food sources require a larger "critical number" of ants to form a stable trail.
The consumption of the food is shown in a plot. The line colors in the plot match the colors of the food piles.
Try different placements for the food sources. What happens if two food sources are equidistant from the nest? When that happens in the real world, ant colonies typically exploit one source then the other (not at the same time).
In this project, the ants use a "trick" to find their way back to the nest: they follow the "nest scent." Real ants use a variety of different approaches to find their way back to the nest. Try to implement some alternative strategies.
The ants only respond to chemical levels between 0.05 and 2. The lower limit is used so the ants aren't infinitely sensitive. Try removing the upper limit. What happens? Why?
uphill-chemical procedure, the ant "follows the gradient" of the chemical. That is, it "sniffs" in three directions, then turns in the direction where the chemical is strongest. You might want to try variants of the
uphill-chemical procedure, changing the number and placement of "ant sniffs."
diffuse primitive lets us diffuse the chemical easily without complicated code.
patch-right-and-ahead is used to make the ants smell in different directions without actually turning.
If you mention this model or the NetLogo software in a publication, we ask that you include the citations below.
For the model itself:
Please cite the NetLogo software as:
Copyright 1997 Uri Wilensky.
This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-sa/3.0/ or send a letter to Creative Commons, 559 Nathan Abbott Way, Stanford, California 94305, USA.
Commercial licenses are also available. To inquire about commercial licenses, please contact Uri Wilensky at firstname.lastname@example.org.
This model was created as part of the project: CONNECTED MATHEMATICS: MAKING SENSE OF COMPLEX PHENOMENA THROUGH BUILDING OBJECT-BASED PARALLEL MODELS (OBPML). The project gratefully acknowledges the support of the National Science Foundation (Applications of Advanced Technologies Program) -- grant numbers RED #9552950 and REC #9632612.
This model was developed at the MIT Media Lab using CM StarLogo. See Resnick, M. (1994) "Turtles, Termites and Traffic Jams: Explorations in Massively Parallel Microworlds." Cambridge, MA: MIT Press. Adapted to StarLogoT, 1997, as part of the Connected Mathematics Project.
This model was converted to NetLogo as part of the projects: PARTICIPATORY SIMULATIONS: NETWORK-BASED DESIGN FOR SYSTEMS LEARNING IN CLASSROOMS and/or INTEGRATED SIMULATION AND MODELING ENVIRONMENT. The project gratefully acknowledges the support of the National Science Foundation (REPP & ROLE programs) -- grant numbers REC #9814682 and REC-0126227. Converted from StarLogoT to NetLogo, 1998.