Sugarscape 1 Immediate Growback
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WHAT IS IT?
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.
HOW IT WORKS
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.
HOW TO USE IT
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.
THINGS TO NOTICE
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.
THINGS TO TRY
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?
NETLOGO FEATURES
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
.
RELATED MODELS
Other models in the NetLogo Sugarscape suite include:
- Sugarscape 2 Constant Growback
- Sugarscape 3 Wealth Distribution
CREDITS AND REFERENCES
Epstein, J. and Axtell, R. (1996). Growing Artificial Societies: Social Science from the Bottom Up. Washington, D.C.: Brookings Institution Press.
HOW TO CITE
If you mention this model in a publication, we ask that you include these citations for the model itself and for the NetLogo software:
- Li, J. and Wilensky, U. (2009). NetLogo Sugarscape 1 Immediate Growback model. http://ccl.northwestern.edu/netlogo/models/Sugarscape1ImmediateGrowback. Center for Connected Learning and Computer-Based Modeling, Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL.
- Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL.
COPYRIGHT AND LICENSE
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 http://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.
Comments and Questions
turtles-own [ sugar ;; the amount of sugar this turtle has metabolism ;; the amount of sugar that each turtles loses each tick vision ;; the distance that this turtle can see in the horizontal and vertical directions vision-points ;; the points that this turtle can see in relative to it's current position (based on vision) ] patches-own [ psugar ;; the amount of sugar on this patch max-psugar ;; the maximum amount of sugar that can be on this patch ] ;; ;; Setup Procedures ;; to setup clear-all create-turtles initial-population [ turtle-setup ] setup-patches reset-ticks end to turtle-setup ;; turtle procedure set color red set shape "circle" move-to one-of patches with [not any? other turtles-here] set sugar random-in-range 5 25 set metabolism random-in-range 1 4 set vision random-in-range 1 6 ;; turtles can look horizontally and vertically up to vision patches ;; but cannot look diagonally at all set vision-points [] foreach n-values vision [? + 1] [ set vision-points sentence vision-points (list (list 0 ?) (list ? 0) (list 0 (- ?)) (list (- ?) 0)) ] run visualization end to setup-patches file-open "sugar-map.txt" foreach sort patches [ ask ? [ set max-psugar file-read set psugar max-psugar patch-recolor ] ] file-close end ;; ;; Runtime Procedures ;; to go if not any? turtles [ stop ] ask patches [ patch-growback patch-recolor ] ask turtles [ turtle-move turtle-eat if sugar <= 0 [ die ] run visualization ] tick end to turtle-move ;; turtle procedure ;; consider moving to unoccupied patches in our vision, as well as staying at the current patch let move-candidates (patch-set patch-here (patches at-points vision-points) with [not any? turtles-here]) let possible-winners move-candidates with-max [psugar] if any? possible-winners [ ;; if there are any such patches move to one of the patches that is closest move-to min-one-of possible-winners [distance myself] ] end to turtle-eat ;; turtle procedure ;; metabolize some sugar, and eat all the sugar on the current patch set sugar (sugar - metabolism + psugar) set psugar 0 end to patch-recolor ;; patch procedure ;; color patches based on the amount of sugar they have set pcolor (yellow + 4.9 - psugar) end to patch-growback ;; patch procedure ;; immediately grow back all of the sugar for the patch set psugar max-psugar end ;; ;; Utilities ;; to-report random-in-range [low high] report low + random (high - low + 1) end ;; ;; Visualization Procedures ;; to no-visualization ;; turtle procedure set color red end to color-agents-by-vision ;; turtle procedure set color red - (vision - 3.5) end to color-agents-by-metabolism ;; turtle procedure set color red + (metabolism - 2.5) end ; Copyright 2009 Uri Wilensky. ; See Info tab for full copyright and license.
There are 9 versions of this model.
Attached files
File | Type | Description | Last updated | |
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Sugarscape 1 Immediate Growback.png | preview | Preview for 'Sugarscape 1 Immediate Growback' | over 11 years ago, by Uri Wilensky | Download |
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Camelia Florela Voinea
Course "Political Attitudes: Modelling & Simulation" (Question)
Hi! I need some well-known models to run as demos for one of my courses on modelling & simulation. Unfortunately, no old model works for Sugarscape as it was written in old NetLogo version. May I kindly ask how can I get a running version of Sugarscape for demo and teaching for my courses? Looking forward to your collaboration, Best wishes, Camelia Florela Voinea, PhD, Assoc. Prof. University of Bucharest
Posted over 2 years ago