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? perc-unhappy-red ;; what percent of the red turtles are unhappy? perc-unhappy-blue ;; what percent of the blue turtles are unhappy? place-for-red place-for-blue haltt time exact rule-code-red rule-code-blue n-blue ] 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 turn ;; true if it's this turtle's turn to move rule ] patches-own [ red-nearby all-nearby blue-nearby ok-for-red ok-for-blue rrule ] breed [ blues ] breed [ reds ] to setup ca set exact false set haltt 0 set time 0 if number > count patches [ user-message (word "This pond only has room for " count patches " turtles.") stop ] ;;change rule descriptions from chooser to codes for convenience if rule-red = "1: any mixture"[set rule-code-red 1] if rule-red = "2: majority of blues"[set rule-code-red 2] if rule-red = "3: reds not minority"[set rule-code-red 3] if rule-red = "4: reds are majority"[set rule-code-red 4] if rule-red = "5: no blues"[set rule-code-red 5] if rule-red = "6: full of reds"[set rule-code-red 6] if rule-red = "7: equal numbers of reds and blues"[set rule-code-red 7] if rule-red = "8: percentages"[set rule-code-red 8] if rule-blue = "1: any mixture"[set rule-code-blue 1] if rule-blue = "2: majority of reds"[set rule-code-blue 2] if rule-blue = "3: blues not minority"[set rule-code-blue 3] if rule-blue = "4: blues are majority"[set rule-code-blue 4] if rule-blue = "5: no reds"[set rule-code-blue 5] if rule-blue = "6: full of blues"[set rule-code-blue 6] if rule-blue = "7: equal numbers of reds and blues"[set rule-code-blue 7] if rule-blue = "8: percentages"[set rule-code-blue 8] ;; create turtles on random patches. ask n-of number patches [ sprout-reds 1 [ set color red set shape "face happy"] ] ;; turn part of the turtles blue set n-blue ((number * %-blue) / 100) ; number of blues if n-blue < 1 [ set n-blue 1 ; make sure that we have at least one blue ] if n-blue > (number - 1) [ set n-blue (number - 1) ; .... and at least one red ] ask n-of n-blue turtles [ set breed blues set color blue set shape "face happy"] update-variables do-plots end to set-sequence ;procedure to determine the sequence of moves among the turtles. Samples only among unhappy turtles to speed up the procedure ask turtles [ set turn false ] if count turtles with [happy? = false] > 0 [ ask one-of turtles with [happy? = false][ set turn true ] ] end to CheckSpaceRed ;procedure to check whether there is at least one place to move to for a red turtle ask patches[ set red-nearby count (reds-on neighbors ) set blue-nearby count (blues-on neighbors) set all-nearby count (turtles-on neighbors) if rule-code-red = 1[ set ok-for-red (count turtles-here = 0) ; any mixture ] if rule-code-red = 2[ set ok-for-red (blue-nearby > (all-nearby / 2) and (count turtles-here = 0)); blues majority ] if rule-code-red = 3[ set ok-for-red (red-nearby >= (all-nearby / 2) and (count turtles-here = 0)) ; reds not minority ] if rule-code-red = 4[ set ok-for-red (red-nearby > (all-nearby / 2) and (count turtles-here = 0)) ; reds majority ] if rule-code-red = 5[ set ok-for-red (blue-nearby = 0 and (count turtles-here = 0)) ; no blues ] if rule-code-red = 6[ set ok-for-red (red-nearby = 8 and (count turtles-here = 0)) ; full of reds ] if rule-code-red = 7[ set ok-for-red (red-nearby = blue-nearby and (count turtles-here = 0)) ; equal numbers ] if rule-code-red = 8[ set ok-for-red (red-nearby >= ( %-similar-wanted-by-red * all-nearby / 100 )) and (count turtles-here = 0) ] ] set place-for-red count patches with [ok-for-red = true] end to CheckSpaceBlue ;procedure to check whether there is at least one place to move to for a blue turtle ask patches[ set blue-nearby count (blues-on neighbors ) set red-nearby count (reds-on neighbors) set all-nearby count (turtles-on neighbors) if rule-code-blue = 1[ set ok-for-blue (count turtles-here = 0) ; any mixture ] if rule-code-blue = 2[ set ok-for-blue (red-nearby > ( all-nearby / 2 ) and (count turtles-here = 0)) ; reds majority ] if rule-code-blue = 3[ set ok-for-blue (blue-nearby >= ( all-nearby / 2 ) and (count turtles-here = 0)) ; blues not minority ] if rule-code-blue = 4[ set ok-for-blue (blue-nearby > ( all-nearby / 2 ) and (count turtles-here = 0)); blues majority ] if rule-code-blue = 5[ set ok-for-blue (red-nearby = 0 and (count turtles-here = 0)) ; no reds ] if rule-code-blue = 6[ set ok-for-blue (blue-nearby = 8 and (count turtles-here = 0)) ; all blues ] if rule-code-blue = 7[ set ok-for-blue (blue-nearby = red-nearby and (count turtles-here = 0)) ; equal numbers ] if rule-code-blue = 8[ set ok-for-blue (blue-nearby >= ( %-similar-wanted-by-blue * all-nearby / 100 )) and (count turtles-here = 0) ] ] set place-for-blue count patches with [ok-for-blue = true] end to go ;if not any? turtles with [not happy?] [ user-message "everybody is happy" ] ;if not any? turtles with [not happy?] [ stop ] update-variables do-plots set haltt 0 if all? turtles [happy?] [stop] if (place-for-red = 0 or perc-unhappy-red = 0) and (place-for-blue = 0 or perc-unhappy-blue = 0 )[stop] update-variables move-unhappy-turtles do-plots set time time + 1 if haltt = 1 [ update-variables stop ] end to halt set haltt 1 end to move-unhappy-turtles ask reds with [ not happy? and turn = true] [ if place-for-red > 0 [ find-new-spot ] ] ask blues with [ not happy? and turn = true] [ if place-for-blue > 0 [ find-new-spot ] ] end to find-new-spot rt random-float 360 fd random-float 1 if color = red[ if any? other turtles-here or [not ok-for-red] of(patch-here) [ find-new-spot ] ;; keep going until we find an unoccupied patch ] if color = blue[ if any? other turtles-here or [not ok-for-blue] of(patch-here) [ find-new-spot ] ;; keep going until we find an unoccupied patch ] setxy pxcor pycor ;; move to center of patch end to update-variables update-rules update-turtles update-globals end to update-turtles ask turtles with [color = red][ ;; in next two lines, we use "neighbors" to test the eight patches ;; surrounding the current patch set rule rule-code-red set similar-nearby count (turtles-on neighbors) with [color = [color] of myself] set other-nearby count (turtles-on neighbors) with [color != [color] of myself] set total-nearby similar-nearby + other-nearby if rule = 1[ set happy? true ] if rule = 2[ set happy? (other-nearby > (total-nearby / 2)) ] if rule = 3[ set happy? (similar-nearby >= ( total-nearby / 2 )) ] if rule = 4[ set happy? (similar-nearby > ( total-nearby / 2 )) ] if rule = 5[ set happy? (other-nearby = 0) ] if rule = 6[ set happy? (similar-nearby = 8) ] if rule = 7[ set happy? (similar-nearby = other-nearby) ] if rule = 8[ set happy? similar-nearby >= ( %-similar-wanted-by-red * total-nearby / 100) ] ] ask turtles with [color = blue][ ;; in next two lines, we use "neighbors" to test the eight patches ;; surrounding the current patch set rule rule-code-blue set similar-nearby count (turtles-on neighbors) with [color = [color] of myself] set other-nearby count (turtles-on neighbors) with [color != [color] of myself] set total-nearby similar-nearby + other-nearby if rule = 1[ set happy? true ] if rule = 2[ set happy? (other-nearby > (total-nearby / 2)) ] if rule = 3[ set happy? (similar-nearby >= (total-nearby / 2)) ] if rule = 4[ set happy? (similar-nearby > (total-nearby / 2)) ] if rule = 5[ set happy? (other-nearby = 0) ] if rule = 6[ set happy? (similar-nearby = 8) ] if rule = 7[ set happy? (similar-nearby = other-nearby) ] if rule = 8[ set happy? similar-nearby >= ( %-similar-wanted-by-blue * total-nearby / 100) ] ] ask turtles with [happy?][ set shape "face happy" ] ask turtles with [not happy?][ set shape "face sad" ] set-sequence end to update-globals let similar-neighbors sum [similar-nearby] of turtles let total-neighbors sum [total-nearby] of turtles if total-neighbors = 0 [ set percent-similar 0 ] if total-neighbors > 0 [ set percent-similar (similar-neighbors / total-neighbors) * 100 ] set percent-unhappy (count turtles with [not happy?]) / (count turtles) * 100 set perc-unhappy-red (count turtles with [not happy? and color = red]) / (count turtles with [color = red]) * 100 set perc-unhappy-blue (count turtles with [not happy? and color = blue]) / (count turtles with [color = blue]) * 100 CheckSpaceRed CheckSpaceBlue end to update-rules ;;change rule descriptions from chooser to codes for convenience if rule-red = "1: any mixture"[set rule-code-red 1] if rule-red = "2: majority of blues"[set rule-code-red 2] if rule-red = "3: reds not minority"[set rule-code-red 3] if rule-red = "4: reds are majority"[set rule-code-red 4] if rule-red = "5: no blues"[set rule-code-red 5] if rule-red = "6: full of reds"[set rule-code-red 6] if rule-red = "7: equal numbers of reds and blues"[set rule-code-red 7] if rule-red = "8: percentages"[set rule-code-red 8] if rule-blue = "1: any mixture"[set rule-code-blue 1] if rule-blue = "2: majority of reds"[set rule-code-blue 2] if rule-blue = "3: blues not minority"[set rule-code-blue 3] if rule-blue = "4: blues are majority"[set rule-code-blue 4] if rule-blue = "5: no reds"[set rule-code-blue 5] if rule-blue = "6: full of blues"[set rule-code-blue 6] if rule-blue = "7: equal numbers of reds and blues"[set rule-code-blue 7] if rule-blue = "8: percentages"[set rule-code-blue 8] end to do-plots set-current-plot "Percent Similar" plot percent-similar set-current-plot "Percent Unhappy" plot percent-unhappy end ; *** NetLogo Model Copyright Notice *** ; ; 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. ; ; Copyright 1998 by 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 converted to NetLogo as part of the project: ; PARTICIPATORY SIMULATIONS: NETWORK-BASED DESIGN FOR SYSTEMS LEARNING IN ; CLASSROOMS. The project gratefully acknowledges the support of the ; National Science Foundation (REPP program) -- grant number REC #9814682. ; Converted from StarLogoT to NetLogo, 2001. Updated 2002. ; ; 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. ; ; In other publications, please use: ; Copyright 1998 by Uri Wilensky. All rights reserved. See ; http://ccl.northwestern.edu/netlogo/models/Segregation ; for terms of use. ; ; *** End of NetLogo Model Copyright Notice *** @#$#@#$#@ GRAPHICS-WINDOW 623 44 1203 645 9 9 30.0 1 10 1 1 1 0 1 1 1 -9 9 -9 9 0 0 1 ticks CC-WINDOW 5 771 1212 866 Command Center 0 MONITOR 282 654 374 699 Percent Unhappy percent-unhappy 1 1 11 MONITOR 9 656 115 701 Percent Similar percent-similar 1 1 11 PLOT 8 479 257 642 Percent Similar time % 0.0 25.0 0.0 100.0 true false PENS "percent" 1.0 0 -2674135 true PLOT 281 478 530 642 Percent Unhappy time % 0.0 25.0 0.0 100.0 true false PENS "percent" 1.0 0 -10899396 true SLIDER 296 156 536 189 number number 2 360 346 2 1 NIL HORIZONTAL BUTTON 199 47 267 80 setup setup NIL 1 T OBSERVER NIL S NIL NIL BUTTON 295 47 364 80 go go T 1 T OBSERVER NIL G NIL NIL SLIDER 8 155 254 188 %-blue %-blue 1 99 50 1 1 % HORIZONTAL SLIDER 323 358 513 391 %-similar-wanted-by-blue %-similar-wanted-by-blue 0 100 30 1 1 % HORIZONTAL MONITOR 382 654 483 699 % Unhappy red perc-unhappy-red 1 1 11 MONITOR 492 655 597 700 % Unhappy blue perc-unhappy-blue 1 1 11 MONITOR 137 656 228 701 Time time 0 1 11 MONITOR 137 712 228 757 Places for red place-for-red 1 1 11 MONITOR 10 712 114 757 Places for blue place-for-blue 1 1 11 CHOOSER 13 298 217 343 rule-red rule-red "1: any mixture" "2: majority of blues" "3: reds not minority" "4: reds are majority" "5: no blues" "6: full of reds" "7: equal numbers of reds and blues" "8: percentages" 2 CHOOSER 12 356 220 401 rule-blue rule-blue "1: any mixture" "2: majority of reds" "3: blues not minority" "4: blues are majority" "5: no reds" "6: full of blues" "7: equal numbers of reds and blues" "8: percentages" 2 SLIDER 321 302 514 335 %-similar-wanted-by-red %-similar-wanted-by-red 0 100 30 1 1 % HORIZONTAL TEXTBOX 219 243 369 261 Preference Settings 14 0.0 1 TEXTBOX 99 269 127 287 Rules 11 0.0 1 TEXTBOX 386 268 464 287 Percentages 11 0.0 1 TEXTBOX 326 401 476 429 To activate percentages, select rule 8 in Rules (left) 11 0.0 1 TEXTBOX 249 442 399 460 Output 14 0.0 1 TEXTBOX 239 109 339 127 Basic Settings 14 0.0 1 TEXTBOX 257 15 407 33 Controls 14 0.0 1 TEXTBOX 87 135 237 153 Percentage blue 11 0.0 1 TEXTBOX 372 136 522 154 Number of inhabitants 11 0.0 1 @#$#@#$#@ WHAT IS IT? ------------ This project is another implementation of Schelling's model of social segregation. It is based on the project "Segregation" from netlogo's standard models library, but some respects closer to Schelling's original formulation of the model, and with some added features. As in the original version the basic assumption is that each inhabitant wants to live next to at least a given number of inhabitants of the same colour. However, in this version the inhabitants move sequentially rather then simultaniously. Moreover, inhabitants only start moving if there is a satisfactory place (patch) available for them somewhere, and settle only at places that meet their requirements. Added features are separate sliders for the preferences of both colors, and the possibility to change parameters and restart the process from an equilibrium situation. HOW IT WORKS ------------- The program is a rather close imitation of Schellings original model. It consists of a "city" made of a square grid, in which two groups of "inhabitants" (or actors) live, the Reds and the Blues. Initially, all inhabitants are randomly distributed around the city. Each inhabitant has a certain number of "neighbors"; these are the actors occupying the eight squares surrounding the square on which the actor "lives". Thus, each inhabitant can have between zero and eight neighbors. Actually, the city is not a square but a 3-dimensional "torus", which means that the upper edge touches to lower edges and the right edge touches the left edge, such that the city has no borders. Now, as in Schelling's model, we let the inhabitants evaluate there current location, based on a certain preference rules. These rules determine whether an actor is happy with his current location or not. In this simulation, we implemented eight different preference rules. What follows is a short description of the rules for the BLUE actors, but they are symmetric for the Reds. "1: any mixture" According to this rule, the blue actors are happy with every mixtures of neighbors. "2: majority of reds" Blue actors are happy if the majority of their neighbors are red. "3: blues not minority" Blue actors are happy if at least half of their neighbors are blue. "4: blues are majority" Blue actors are happy if more than half of their neighbors are blue. "5: no reds" Blue actors are happy only if they have no red neighbors at all. "6: full of blues" Blue actors are happy only if they have eight blue neighbors. "7: egual numbers of reds and blues" Blue actors are happy only if they have as many blue neighbors as they have red neighbors. "8: percentages" This is actually not really a rule. It means that the preference is determined by a certain percentage, which you have to set separately (as we'll explain below). Blue actors are happy only if the share of similar (=blue) neighbors is AT LEAST this percentage. Thus, if the percentage is set at 40%, Blues are happy with their location if 40% or more of their neighbors are also Blues. The dynamic process works as follows: In every step, every inhabitant decides whether she is happy with her current location or not (you will see their faces change accordingly). Then, the computer checks how many empty places exist that would satisfy the preferences of Reds and Blues, respectively. Next, one unhappy actor is randomly selected. If there are places available, she will start to move around in a random fashion until she has found a place that satisfies her preferences. This process is repeated until: - There are no good places for Blue Left, OR all Blues are happy AND - There are no good places for Red Left, OR all Reds are happy. (Verify for yourself that this is indeed an equilibrium). HOW TO USE IT -------------- 1. CHOOSE THE BASIC SETTINGS Use the slider labeled "Number of inhabitants" to set the total number of inhabitants in the city, and the %-BLUE slider to change the percentage of blue inhabitants. Use the "rule-red" and "rule-blue" buttons to choose the preferences of the red and blue inhabitants, respectively. If you change the "Type of rule" button to "%-(Left)", you can use the sliders on the left to choose the preferences as percentages rather than rules. When you're done, click the SETUP button once, which creates a random starting situation. (This will not change anything on the screen yet). When you're done, press the "Setup" button in the section "Controls" (pressing "s" on your keyboard also works). This will create a starting situation according to your specifications, with the blue and red inhabitants distributed randomly across the city. 2. CHOOSE THE INHABITANTS' PREFERENCES Now choose how the inhabitants evaluate their neighborhoods. You can change the preferences of both the red and blue inhabitants separately, using the drop-down menus named "rule-red" and "rule-blue", under "Rules" in the section "Preference Settings". If you want to use precentages rather than fixed rules (see above), you first need to select Rule 8 under rules. Then, you can select a percentage using the percentage sliders on the right. If Rule 8 is not selected, the percentage sliders have no effect. 3. RUN THE SIMULATION Now you are ready to start the simulation. Click GO (or press "g") under "Controls" to start the simulation. One by one unhappy inhabitants move to a patch that meets their requirements, as long as suitable places are available. To stop the process, you can click the GO button again. After the process has settled down, you may change the preferences of the inhabitants, and continue the simulation to by pressing GO again. 4. READ THE RESULTS The "Percent Similar" monitor shows the average percentage of same-color neighbors for each inhabitant; this is our measure of segregation. It starts at about 0.5, since each inhabitant starts (on average) with an equal number of red and blue inhabitants as neighbors. The "Percent Unhappy" monitors show the percent of inhabitants that have fewer same-color neighbors than they want (and thus want to move) for each. The total percentage unhappy is plotted. Moreover, each inhabitant also shows it's mood. "Places for red" and "Places for blue" show the number of satisfactory places available for each color. It may happen that some inhabitants are still unhappy while there are no longer any places available for them. It that case they just don't move. CREDITS AND REFERENCES ---------------------- Schelling, T. (1978). Micromotives and Macrobehavior. New York: Norton. This model is inspired on: 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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