NetLogo Models Library:
Note: If you download the NetLogo application, every model in the Models Library is included.
This first model in the NetLogo Sugarscape suite implements Epstein & Axtell's Sugarscape Immediate Growback model, as described in chapter 2 of their book Growing Artificial Societies: Social Science from the Bottom Up. It simulates a population with limited, spatially-distributed resources available.
Each patch contains some sugar, the maximum amount of which is predetermined. At each tick, each patch grows back fully to have the maximum amount of sugar. The amount of sugar a patch currently contains is indicated by its color; the darker the yellow, the more sugar.
At setup, agents are placed at random within the world. Each agent can only see a certain distance horizontally and vertically. At each tick, each agent will move to the nearest unoccupied location within their vision range with the most sugar, and collect all the sugar there. If its current location has as much or more sugar than any unoccupied location it can see, it will stay put.
Agents also use (and thus lose) a certain amount of sugar each tick, based on their metabolism rates. If an agent runs out of sugar, it dies.
Set the INITIAL-POPULATION slider before pressing SETUP. This determines the number of agents in the world.
Press SETUP to populate the world with agents and import the sugar map data. GO will run the simulation continuously, while GO ONCE will run one tick.
The VISUALIZATION chooser gives different visualization options and may be changed while the GO button is pressed. When NO-VISUALIZATION is selected all the agents will be red. When COLOR-AGENTS-BY-VISION is selected the agents with the longest vision will be darkest and, similarly, when COLOR-AGENTS-BY-METABOLISM is selected the agents with the lowest metabolism will be darkest.
The four plots show the world population over time, the distribution of sugar among the agents, the mean vision of all surviving agents over time, and the mean metabolism of all surviving agents over time.
After 20 ticks or so, many agents are no longer moving or are only moving a little. This is because the agents have reached places in the world where they can no longer see better unoccupied locations near them. Since all sugar grows back instantaneously each tick, agents tend to remain on the same patch.
Agents tend to congregate in "layers" around borders where sugar production levels change. This unintended behavior comes from the limitation of the agents' vision ranges. Agents that cannot see past the current sugar production grounds have no incentive to move, and so each agent only moves to the closest location with more sugar. This effect is more less apparent depending on the initial population.
Try varying the initial POPULATION. What effect does the initial POPULATION have on the final stable population? Does it have an effect on the distribution of agent properties, such as vision and metabolism?
All of the Sugarscape models create the world by using
file-read to import data from an external file,
sugar-map.txt. This file defines both the initial and the maximum sugar value for each patch in the world.
Since agents cannot see diagonally we cannot use
in-radius to find the patches in the agents' vision. Instead, we use
Other models in the NetLogo Sugarscape suite include:
Epstein, J. and Axtell, R. (1996). Growing Artificial Societies: Social Science from the Bottom Up. Washington, D.C.: Brookings Institution Press.
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 2009 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 email@example.com.