globals [
  percent-similar  ;; on the average, what percent of a turtle's neighbors
                   ;; are the same color as that turtle?
  percent-unhappy  ;; 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
]

patches-own [
  reds-nearby   ;; how many neighboring patches have a red turtle?
  greens-nearby ;; ditto for green turtles
  blues-nearby  ;; mnb
  
  total-nearby  ;; sum of previous two variables
]

to setup
  ca
  cct number
  
  [
    setxy (random screen-size-x)  ;; randomize the turtle locations
          (random screen-size-y)
    ifelse who <= (number / 3)     ;; turn half the turtles red, the others green
      [ set color red ]
      [ ifelse who > (number / 3) and who <= ((number / 3) * 2)
          [ set color green ]
          [ set color blue ] ]
          
      if any other-turtles-here     ;; make sure each turtle is in its own patch
      [ find-new-spot ]
  ]
  update-variables
  do-plots
end

to go
  move-unhappy-turtles
  update-variables
  do-plots
  if not any turtles with [not happy?] [ stop ]
end

to move-unhappy-turtles
  ask turtles [
    if not happy?
      [ find-new-spot ]
  ]
end

to find-new-spot
  rt random 360
  fd random 10
  if any other-turtles-here
    [ find-new-spot ]          ;; keep going until we find an unoccupied patch
end

to update-variables
  update-patches
  update-turtles
  update-globals
end

to update-patches
  ask patches [
    ;; in next two lines, we use "neighbors" to test the eight patches surrounding
    ;; the current patch
    
    set reds-nearby count neighbors with [any turtles-here with [color = red]]
    set greens-nearby count neighbors with [any turtles-here with [color = green]]
    
    set blues-nearby count neighbors with [any turtles-here with [color = blue]] ;; mnb
    
    set total-nearby reds-nearby + greens-nearby + blues-nearby   ;;mnb
  ]
end

to update-turtles
  ask turtles [
    if color = red
      [ set happy? reds-nearby >= ( %-similar-wanted-red * total-nearby / 100 ) ]
    if color = green
      [ set happy? greens-nearby >= ( %-similar-wanted-green * total-nearby / 100 ) ]
    if color = blue
      [ set happy? blues-nearby >= ( %-similar-wanted-blue * total-nearby / 100) ]
      ]
end

to update-globals
  locals [ similar-neighbors total-neighbors ]
  set similar-neighbors
      sum values-from turtles with [color = red] [reds-nearby] +
      sum values-from turtles with [color = green] [greens-nearby] +
      sum values-from turtles with [color = blue] [blues-nearby]  ;;mnb367
      
          set total-neighbors
      sum values-from turtles [total-nearby]
  set percent-similar (similar-neighbors / total-neighbors) * 100
  set percent-unhappy (count turtles with [not happy?]) / (count turtles) * 100
end

to do-plots
  set-current-plot "Percent Similar"
  plot percent-similar
  set-current-plot "Percent Unhappy"
  plot percent-unhappy

  
end

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New Additions (Jan 03)

There are now three different colors of turtles in the pond.  While you can change their desired amount of similar turtles for each color, the default setting is that blue turtles pretty much don't care what they are around, and red turtles do care.
If blue turtles were happy, they were unlikely to move much, and since red turtles were almost always unhappy unless there were enough red turtles, there would either be a definite empty space separation around all red turtles, or the red turtles would never be happy and the model would not resolve itself.  After running it, I found this to be mostly true.





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 "Percent Similar" monitor shows the average percentage of same-color neighbors for each turtle. It starts at about 0.5, since each turtle starts (on average) with an equal number of red and green turtles as neighbors. The "Percent 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?


NETLOGO FEATURES
----------------
In the UPDATE-GLOBALS procedure, note the use of SUM, COUNT, VALUES-FROM, and WITH to compute the percentages displayed in the monitors and plots.


CREDITS AND REFERENCES
----------------------
Schelling, T. (1978). Micromotives and Macrobehavior. New York: Norton.
Seee 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. (1998).  NetLogo Segregation model. http://ccl.northwestern.edu/netlogo/models/Segregation. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.
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NetLogo 1.2beta2
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