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This second model in the NetLogo Sugarscape suite implements Epstein & Axtell's Sugarscape Constant 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. It differs from Sugarscape 1 Immediate Growback in that the growback of sugar is gradual rather than instantaneous.
Each patch contains some sugar, the maximum amount of which is predetermined. At each tick, each patch regains one unit of sugar, until it reaches the maximum amount. 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.
The world has a carrying capacity, which is lower than the initial population of the world. Agents who are born in sugarless places or who consume more sugar than the land cannot be supported by the world, and die. Other agents die from competition - although some places in the world have enough sugar to support them, the sugar supply is limited and other agents may reach and consume it first.
As the population stabilizes, the average vision increases while the average metabolism decreases. Agents with lower vision cannot find the better sugar patches, while agents with high metabolism cannot support themselves. The death of these agents causes the attribute averages to change.
How dependent is the carrying capacity on the initial population size? Is there a direct relationship?
How does changing the amount or rate of sugar growback affect the behavior of the model?
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 at-points
.
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 uri@northwestern.edu.
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