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## NetLogo User Community Models

WHAT IS IT?

This project models the behavior of two types of turtles in a mythical pond. The red turtles and green turtles get along with one another. But each turtle wants to make sure that it lives near some of "its own." That is, each red turtle wants to live near at least some red turtles, and each green turtle wants to live near at least some green turtles. The simulation shows how these individual preferences ripple through the pond, leading to large-scale patterns.

This project was inspired by Thomas Schelling's writings about social systems (such as housing patterns in cities).

HOW TO USE IT

Click the SETUP button to set up the turtles. There are equal numbers of red and green turtles. The turtles move around until there is at most one turtle on a patch. Click GO to start the simulation. If turtles don't have enough same-color neighbors, they jump to a nearby patch.

The NUMBER slider controls the total number of turtles. (It takes effect the next time you click SETUP.) The %-SIMILAR-WANTED slider controls the percentage of same-color turtles that each turtle wants among its neighbors. For example, if the slider is set at 30, each green turtle wants at least 30% of its neighbors to be green turtles.

The % SIMILAR monitor shows the average percentage of same-color neighbors for each turtle. It starts at about 50%, since each turtle starts (on average) with an equal number of red and green turtles as neighbors. The % UNHAPPY monitor shows the percent of turtles that have fewer same-color neighbors than they want (and thus want to move). Both monitors are also plotted.

THINGS TO NOTICE

When you execute SETUP, the red and green turtles are randomly distributed throughout the pond. But many turtles are "unhappy" since they don't have enough same-color neighbors. The unhappy turtles jump to new locations in the vicinity. But in the new locations, they might tip the balance of the local population, prompting other turtles to leave. If a few red turtles move into an area, the local green turtles might leave. But when the green turtles move to a new area, they might prompt red turtles to leave that area.

Over time, the number of unhappy turtles decreases. But the pond becomes more segregated, with clusters of red turtles and clusters of green turtles.

In the case where each turtle wants at least 30% same-color neighbors, the turtles end up with (on average) 70% same-color neighbors. So relatively small individual preferences can lead to significant overall segregation.

THINGS TO TRY

Try different values for %-SIMILAR-WANTED. How does the overall degree of segregation change?

If each turtle wants at least 40% same-color neighbors, what percentage (on average) do they end up with?

EXTENDING THE MODEL

Incorporate social networks into this model. For instance, have unhappy turtles decide on a new location based on information about what a neighborhood is like from other turtles in their network.

Change the rules for turtle happiness. One idea: suppose that the turtles need some minimum threshold of "good neighbors" to be happy with their location. Suppose further that they don't always know if someone makes a good neighbor. When they do, they use that information. When they don't, they use color as a proxy -- i.e., they assume that turtles of the same color make good neighbors.

NETLOGO FEATURES

N-OF and SPROUT are used to create turtles while ensuring no patch has more than one turtle on it.

When a turtle moves, MOVE-TO is used to move the turtle to the center of the patch it eventually finds.

CREDITS AND REFERENCES

Schelling, T. (1978). Micromotives and Macrobehavior. New York: Norton.
See also a recent Atlantic article: Rauch, J. (2002). Seeing Around Corners; The Atlantic Monthly; April 2002;Volume 289, No. 4; 35-48. http://www.theatlantic.com/issues/2002/04/rauch.htm

To refer to this model in academic publications, please use: Wilensky, U. (1997). NetLogo Segregation model. http://ccl.northwestern.edu/netlogo/models/Segregation. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.