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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).
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.
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.
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?
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.
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.
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
If you mention this model in an academic publication, we ask that you include these citations for the model itself and for the NetLogo software:
- 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.
- Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.
In other publications, please use:
Copyright 1997 Uri Wilensky. All rights reserved.
Permission to use, modify or redistribute this model is hereby granted, provided that both of the following requirements are followed:
a) this copyright notice is included.
b) this model will not be redistributed for profit without permission from Uri Wilensky. Contact Uri Wilensky for appropriate licenses for redistribution for profit.
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 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, 2001.
globals [ percent-similar ;; on the average, what percent of a turtle's neighbors ;; are the same color as that turtle? av-happy ;; what percent of the turtles are unhappy? ] turtles-own [ happy ;; for each turtle, indicates whether at least %-similar-wanted percent of ;; that turtles' neighbors are the same color as the turtle similar-nearby ;; how many neighboring patches have a turtle with my color? other-nearby ;; how many have a turtle of another color? total-nearby ;; sum of previous two variables num-tries moving-threshold ] to setup clear-all if number > count patches [ user-message (word "This pond only has room for " count patches " turtles.") stop ] ;; create turtles on random patches. ask n-of number patches [ sprout 1 [ set shape "circle" ifelse same-thres? [set moving-threshold %-similar-wanted / 100] [set moving-threshold random-float %-similar-wanted / 100] ]] ;; turn half the turtles green ask n-of (number * percent-square / 100) turtles [ set shape "square" ifelse same-thres? [set moving-threshold %-similar-wanted / 100] [set moving-threshold random-float %-similar-wanted / 100]] update-variables do-plots end to go ; move-unhappy-turtles update-variables move-turtles tick do-plots end to move-turtles ask turtles [ ; if (random-float 1.0 < 1 / (1 + exp (- (happy - %-similar-wanted / 100)))) if (happy < moving-threshold) [ find-new-spot ] ] end to find-new-spot let x 0 if ((num-tries > 100) and not any? other turtles-here) [ move-to patch-here stop] rt random-float 360 fd random-float 10 ifelse any? other turtles-here [ find-new-spot ] [ ;; keep going until we find an unoccupied patch set num-tries num-tries + 1 set similar-nearby count (turtles-on neighbors) with [shape = [shape] of myself] set other-nearby count (turtles-on neighbors) with [shape != [shape] of myself] set total-nearby similar-nearby + other-nearby ifelse (total-nearby = 0) or (similar-nearby / total-nearby > happy) [ move-to patch-here ;; move to center of patch ] [find-new-spot] ] end to update-variables update-turtles update-globals end to update-turtles let x 0 ask turtles [ ;; in next two lines, we use "neighbors" to test the eight patches ;; surrounding the current patch set num-tries 0 set similar-nearby count (turtles-on neighbors) with [shape = [shape] of myself] set other-nearby count (turtles-on neighbors) with [shape != [shape] of myself] set total-nearby similar-nearby + other-nearby ifelse (total-nearby > 0) [ set x (similar-nearby / total-nearby - %-similar-wanted / 100) set happy similar-nearby / total-nearby ] [ set x 0 set happy 1] ; set happy 1 / (1 + exp (- x)) if (shape = "square") [set color scale-color (red + 2) happy 0 1] if (shape = "circle") [set color scale-color (blue + 2) happy 0 1] ; print happy ] end to update-globals let similar-neighbors sum [similar-nearby] of turtles let total-neighbors sum [total-nearby] of turtles set percent-similar (similar-neighbors / total-neighbors) * 100 set av-happy mean [happy] of turtles end to do-plots set-current-plot "Percent Similar" plot percent-similar set-current-plot "av. happiness" plot av-happy * 100 end ; Copyright 1997 Uri Wilensky. All rights reserved. ; The full copyright notice is in the Information tab.