globals [ Brown-box NotRecyclable Paper_NotRecycled Plastic&Glass_NotRecycled Not-recyclable Blue-box Paper Recyclable_Paper Not-recyclable_Paper Gray-box Plastic&Glass Recyclable_Plastic&Glass Not-recyclable_Plastic&Glass ; they rapresent the common baskets and their content. blue-box-D gray-box-D brown-box-D ; they rapresent the collection domestic baskets of the diligents brown-box-N ; it rapresents the collection domestic baskets of the negligents blue-box-B gray-box-B brown-box-B ; they rapresent the collection domestic baskets of the blunderers paper-D paper-N paper-B ; paper-D is the ricyclable paper produced by Diligent people plastic-and-glass-D plastic-and-glass-N plastic-and-glass-B ; plastic-and-glass-D is the recyclable plastic (or glass) produced by Diligent people. not-recyclable-D not-recyclable-N not-recyclable-B ; paper (or plastic/glass) not recyclable is part of not recyclable trash produced by people. X ; X is the share of not recyclable rubbish considereted recyclable paper by blunderers. Y ; Y is the share of not recyclable rubbish considereted recyclable plastic/glass by blunderers. J ; J is a share of paper basket removed by dustmen because not recyclable: ;; it can be equal to or over X if a share of recyclable paper has been demaged by X. percentage-diligents percentage-negligents percentage-blunderers Stock plastic&glass-stock paper-stock not-recyclable-stock ; the stocks represent the amount arriving in rubbish dump ready for recycling. ] turtles-own [ peoples next-doors responsibility Probability-to-improve Probability-to-worsen ] breed [diligents diligent] breed [negligents negligent] breed [blunderers blunderer] ;-------------------------------------------------------------------------------------- to Setup clear-all setup-turtles do-plot do-plots end ;-------------------------------------------------------------------------------------- to Go tick produce-rubbish differentiation collection imitation-effect update-turtles update-boxes do-plot do-plots if (ticks = 260) [stop] if (count turtles with [color = yellow] = 100) [stop] if (count turtles with [color = red] = 100) [stop] if (count turtles with [color = green] = 100) [stop] end ;-------------------------------------------------------------------------------------- to setup-turtles create-diligents initial_number_of_diligents ask diligents [set shape "house" set size 1.4 set color green setxy random-xcor random-ycor set peoples (1 + (random 7))] create-negligents initial_number_of_negligents ask negligents [set shape "house" set size 1.4 set color red setxy random-xcor random-ycor set peoples (1 + (random 7))] create-blunderers initial_number_of_blunderers ask blunderers [set shape "house" set size 1.4 set color yellow setxy random-xcor random-ycor set peoples (1 + (random 7))] end ;-------------------------------------------------------------------------------------- to produce-rubbish if (count turtles with [color = green]) != 0 [ask turtles with [color = green] [set paper-D (random-float 0.4) * 7 * peoples set plastic-and-glass-D (random-float 1)* 7 * peoples set not-recyclable-D (random-float 0.3)* 7 * peoples] ] ; we assume a paper production greater than or equal to 0 but strictly less than 400 grams per person per day ; so paper-D is a weekly production of paper per house and so on. if (count turtles with [color = red]) != 0 [ask turtles with [color = red] [set paper-N (random-float 0.4) * 7 * peoples set plastic-and-glass-N (random-float 1)* 7 * peoples set not-recyclable-N (random-float 0.3)* 7 * peoples] ] if (count turtles with [color = yellow]) != 0 [ask turtles with [color = yellow] [set paper-B (random-float 0.4) * 7 * peoples set plastic-and-glass-B (random-float 1)* 7 * peoples set not-recyclable-B (random-float 0.3)* 7 * peoples] ] end ;-------------------------------------------------------------------------------------- to differentiation if (count turtles with [color = yellow]) != 0 [ask turtles with [color = yellow] [set X (random-float 0.4) set Y (random-float 0.2)] ; blunderers put within ricyclable trash a random share of not recyclable rubbish. ; we assume not recyclable paper a share <= than/to 40% of not recyclable trash and not recyclable plastic a share <= than/to 20% of not recyclable trash. ifelse awareness-effect? ; with awareness effect: [ask one-of turtles with [color = yellow] ; not everyone will join [set responsibility (random-float 1) set Probability-to-improve (random-float 1) ; consider a distribution function: if the random drawing belongs to the range of probability, the event occurred. ; blunderers have probability 4% to riduce their mistake if Probability-to-improve < 0.05 + (0.05 * responsibility) and Probability-to-improve > 0.01 + (0.01 * responsibility) [let alfa((random-float 1) * X) let beta ((random-float 1) * X) ;alfa and beta tell how much we reduce the error set blue-box-B (paper-B + (not-recyclable-B * (X - alfa ))) set gray-box-B (plastic-and-glass-B + (not-recyclable-B * (Y - beta))) set brown-box-B (not-recyclable-B * (1 - (X - alfa ) - (Y - beta))) ] ; and probability 1% to become diligents. if Probability-to-improve < 0.01 + (0.01 * responsibility) [ask one-of turtles with [color = yellow] [set color green]] ] ] ; without awareness effect : [set blue-box-B (paper-B + (not-recyclable-B * X)) set gray-box-B (plastic-and-glass-B + (not-recyclable-B * Y)) set brown-box-B (not-recyclable-B * (1 - X - Y)) ] ] if (count turtles with [color = green]) != 0 [ ask turtles with [color = green] [ set blue-box-D (paper-D) set gray-box-D (plastic-and-glass-D) set brown-box-D (not-recyclable-D) ] ; diligents people differentiate correctly: their paper box contains only ricyclable paper. ] if (count turtles with [color = red]) != 0 [ask turtles with [color = red] [ifelse awareness-effect? ; with awareness effect [ask one-of turtles with [color = red] [set responsibility (random-float 1) set Probability-to-improve (random-float 1) ; negligents have probability 0.1% / 0.2% to become blunderers. ifelse Probability-to-improve < 0.0011 + (0.0011 * responsibility) and Probability-to-improve > 0.0001 + (0.0001 * responsibility) [ask one-of turtles with [color = red] [set color yellow]] ; and probability 0.01% to become diligents. [if Probability-to-improve < 0.001 + (0.001 * responsibility) [ask one-of turtles with [color = red] [set color green]] ] ] ] ; without awareness effect negligents people do not differentiate: they put everything in one rubbish box. [set brown-box-N (paper-N + plastic-and-glass-N + not-recyclable-N) ] ] ] end ;-------------------------------------------------------------------------------------- to collection set J (random-float 0.4) set Brown-box (Brown-box + brown-box-D + brown-box-N + brown-box-B) set Blue-box (Blue-box + blue-box-D + blue-box-B) set Gray-box (Gray-box + gray-box-D + gray-box-B) ; this function is intented to return the cumulated amount of rubbish per common specific baskets. ifelse dustman-work? ; this function manages the activities of dustman [set not-recyclable-stock ( not-recyclable-stock + ( blue-box-B * J) + brown-box-D + brown-box-N + brown-box-B) set paper-stock (paper-stock + (blue-box-B * (1 - J)) + blue-box-D) ; a share of paper basket of blunderer is removed by dustmen because not recyclable set plastic&glass-stock (plastic&glass-stock + (gray-box-B * (1 - Y)) + gray-box-D) ; in this case the error is completely removed because the not recyclable plastic does not damage that recyclable. set Stock (paper-stock + plastic&glass-stock + not-recyclable-stock) ] ; without dustman J and Y are null [set not-recyclable-stock (not-recyclable-stock + brown-box-D + brown-box-N + brown-box-B) set paper-stock (paper-stock + blue-box-B + blue-box-D) set plastic&glass-stock (plastic&glass-stock + gray-box-B + gray-box-D) set Stock (paper-stock + plastic&glass-stock + not-recyclable-stock) ] end ;-------------------------------------------------------------------------------------- to imitation-effect if (count turtles with [color = green]) > 0 [ask n-of (random (0.25 * count turtles with [color = green])) turtles with [color = green] ; only a small share of green turtles is selected [if imitation-effect? ; diligents makes a list of neighbors who differentiate and compares them with who do not differentiate. [ifelse awareness-effect? ; with awareness effect [set next-doors list (count (turtles in-radius 3) with [color = yellow]) (count (turtles in-radius 3) with [color = green]) set responsibility (random-float 1) set Probability-to-worsen (random-float 1) ; diligents can only get worse. ; their have (conditional) probability 4% to become negligents ifelse sum next-doors < (count (turtles in-radius 3) with [color = red]) and Probability-to-worsen < 0.04 + (0.04 * responsibility) and (count turtles with [color = green]) != 0 [ask n-of (random (0.25 * count turtles with [color = green])) turtles with [color = green] [set color red]] ; and probability 10% to become blunderers [if max next-doors = (count turtles in-radius 3 with [color = yellow]) and Probability-to-worsen > 0.04 + (0.04 * responsibility) and Probability-to-worsen < 0.10 + (0.10 * responsibility) and (count turtles with [color = green]) != 0 [ask n-of (random (0.25 * count turtles with [color = green])) turtles with [color = green][set color yellow]] ] ] ; without awareness effect [set next-doors list (count (turtles in-radius 3) with [color = yellow]) (count (turtles in-radius 3) with [color = green]) set responsibility (random-float 1) set Probability-to-worsen (random-float 1) ; diligents have (conditional) probability 10% to become negligents ifelse sum next-doors < (count (turtles in-radius 3) with [color = red]) and Probability-to-worsen < 0.10 + (0.10 * responsibility) and (count turtles with [color = green]) != 0 [ask n-of (random (0.25 * count turtles with [color = green])) turtles with [color = green] [set color red]] ; and probability 12% to become blunderers. [if max next-doors = (count turtles in-radius 3 with [color = yellow]) and Probability-to-worsen > 0.10 + (0.10 * responsibility) and Probability-to-worsen < 0.22 + (0.22 * responsibility) and (count turtles with [color = green]) != 0 [ask n-of (random (0.25 * count turtles with [color = green])) turtles with [color = green][set color yellow]] ] ] ] ] ] if (count turtles with [color = red]) > 0 [ask n-of (random (0.25 * count turtles with [color = red])) turtles with [color = red] [if imitation-effect? [ifelse awareness-effect? ; with awareness effect [set next-doors list (count (turtles in-radius 6) with [color = yellow]) ; the radius differs because we assume that negligents have more awe. (count (turtles in-radius 6) with [color = green]) set responsibility (random-float 1) set Probability-to-improve (random-float 1) ; negligents can only improve. ; their have (conditional) probability 5% to become diligents ifelse sum next-doors > (count (turtles in-radius 6) with [color = red]) and Probability-to-improve < 0.05 + (0.05 * responsibility) and (count turtles with [color = red]) != 0 [ask n-of (random (0.25 * count turtles with [color = red])) turtles with [color = red][set color green]] ; and (conditional) probability 10% to become blunderers. [if sum next-doors > (count (turtles in-radius 6) with [color = red]) and Probability-to-improve > 0.05 + (0.05 * responsibility) and Probability-to-improve < 0.15 + (0.15 * responsibility) and (count turtles with [color = red]) != 0 [ask n-of (random (0.25 * count turtles with [color = red])) turtles with [color = red] [set color yellow]] ]] ; without awareness effect [set next-doors list (count (turtles in-radius 6) with [color = yellow]) (count (turtles in-radius 6) with [color = green]) set responsibility (random-float 1) set Probability-to-improve (random-float 1) ; negligents have (conditional) probability 0.1% to become diligents. ifelse sum next-doors > (count (turtles in-radius 6) with [color = red]) and Probability-to-improve < 0.001 + (0.001 * responsibility) and (count turtles with [color = red]) != 0 [ask n-of (random (0.25 * count turtles with [color = red])) turtles with [color = red][set color green]] ; and (conditional) probability 2% to become blunderers. [if sum next-doors > (count (turtles in-radius 6) with [color = red]) and Probability-to-improve > 0.001 + (0.001 * responsibility) and Probability-to-improve < 0.021 + (0.021 * responsibility) and (count turtles with [color = red]) != 0 [ask n-of (random (0.25 * count turtles with [color = red])) turtles with [color = red] [set color yellow]] ] ] ] ] ] if (count turtles with [color = yellow]) > 0 [ask n-of (random (0.25 * count turtles with [color = yellow])) turtles with [color = yellow] [if imitation-effect? ; blunderers may be better or worse: [ifelse awareness-effect? ; with awareness effect [set next-doors list (count (turtles in-radius 6) with [color = green]) (count (turtles in-radius 6) with [color = yellow]) set responsibility (random-float 1) set Probability-to-worsen (random-float 1) set Probability-to-improve(random-float 1) ; they become negligents with (conditional) probability 0.01% , ifelse sum next-doors < (count (turtles in-radius 6) with [color = red]) and Probability-to-worsen < 0.0001 + (0.0001 * responsibility) and (count turtles with [color = yellow])!= 0 [ask n-of (random (0.25 * count turtles with [color = yellow])) turtles with [color = yellow][set color red]] ; or diligents with (conditional) probability 30%. [if max next-doors = (count (turtles in-radius 6) with [color = green]) and Probability-to-improve < 0.30 + (0.30 * responsibility) and (count turtles with [color = yellow])!= 0 [ask n-of (random (0.25 * count turtles with [color = yellow])) turtles with [color = yellow][set color green]] ]] ; without awareness effect [set next-doors list (count(turtles in-radius 6) with [color = green]) (count (turtles in-radius 6) with [color = yellow]) set responsibility (random-float 1) set Probability-to-worsen (random-float 1) set Probability-to-improve(random-float 1) ; they becomenegligents with (conditional) probability 20% , ifelse sum next-doors < (count (turtles in-radius 6) with [color = red]) and Probability-to-worsen < 0.20 + (0.20 * responsibility) and (count turtles with [color = yellow])!= 0 [ask n-of (random (0.25 * count turtles with [color = yellow])) turtles with [color = yellow][set color red]] ; or diligents with (conditional) probability 0.01%. [if max next-doors = (count (turtles in-radius 6) with [color = green]) and Probability-to-improve < 0.0001 + (0.0001 * responsibility) and (count turtles with [color = yellow])!= 0 [ask n-of (random (0.25 * count turtles with [color = yellow])) turtles with [color = yellow] [set color green]] ] ] ] ] ] end ;-------------------------------------------------------------------------------------- to do-plot set-current-plot "Rubbish dump" set-current-plot-pen "Paper stock" plot paper-stock set-current-plot-pen "Plastic & glass stock" plot plastic&glass-stock set-current-plot-pen "Not recyclable stock" plot not-recyclable-stock end ;-------------------------------------------------------------------------------------- to update-turtles let total (count turtles with [color = yellow] + count turtles with [color = red] + count turtles with [color = green]) if total != 0 [set percentage-diligents ((count turtles with [color = green]) / total)* 100 set percentage-negligents ((count turtles with [color = red]) / total)* 100 set percentage-blunderers ((count turtles with [color = yellow]) / total)* 100 ] end ;-------------------------------------------------------------------------------------- to update-boxes set Recyclable_Paper (Recyclable_Paper + paper-D + paper-B) set Not-recyclable_Paper (Not-recyclable_Paper + not-recyclable-B * X) set Paper (Recyclable_Paper + Not-recyclable_Paper) set Recyclable_Plastic&Glass (Recyclable_Plastic&Glass + plastic-and-glass-D + plastic-and-glass-B) set Not-recyclable_Plastic&Glass (Not-recyclable_Plastic&Glass + (not-recyclable-B * Y)) set Plastic&Glass (Recyclable_Plastic&Glass + Not-recyclable_Plastic&Glass) set Paper_NotRecycled (Paper_NotRecycled + paper-N) set Plastic&Glass_NotRecycled (Plastic&Glass_NotRecycled + plastic-and-glass-N) set Not-recyclable (Not-recyclable + (not-recyclable-B * (1 - X - Y)) + not-recyclable-D + not-recyclable-N) set NotRecyclable (Paper_NotRecycled + Plastic&Glass_NotRecycled + Not-recyclable) end ;-------------------------------------------------------------------------------------- to do-plots set-current-plot "Blue box" set-current-plot-pen "R-Paper" plot Recyclable_Paper set-current-plot-pen "Not R-Paper" plot Not-recyclable_Paper set-current-plot "Brown box" set-current-plot-pen "P-Not recycled" plot Paper_NotRecycled set-current-plot-pen "P&g-Not recycled" plot Plastic&Glass_NotRecycled set-current-plot-pen "Not recyclable" plot Not-recyclable set-current-plot "Gray box" set-current-plot-pen "R-Plastic & glass" plot Recyclable_Plastic&Glass set-current-plot-pen "Not R-Plastic & glass" plot Not-recyclable_Plastic&Glass set-current-plot "Composition" set-current-plot-pen "%Diligents" plot percentage-diligents set-current-plot-pen "%Negligents" plot percentage-negligents set-current-plot-pen "%Blunderers" plot percentage-blunderers end @#$#@#$#@ GRAPHICS-WINDOW -2 58 457 538 16 16 13.61 1 10 1 1 1 0 1 1 1 -16 16 -16 16 1 1 1 ticks CC-WINDOW 5 614 1253 709 Command Center 0 SLIDER 1072 360 1243 393 initial_number_of_diligents initial_number_of_diligents 0 100 40 1 1 NIL HORIZONTAL BUTTON 77 10 159 48 NIL Setup NIL 1 T OBSERVER NIL NIL NIL NIL BUTTON 162 10 246 48 NIL Go T 1 T OBSERVER NIL NIL NIL NIL SLIDER 1073 426 1244 459 initial_number_of_negligents initial_number_of_negligents 0 100 20 1 1 NIL HORIZONTAL SLIDER 1073 495 1244 528 initial_number_of_blunderers initial_number_of_blunderers 0 100 40 1 1 NIL HORIZONTAL PLOT 767 10 1222 214 Rubbish dump weeks grams 0.0 10.0 0.0 10.0 true true PENS "Paper stock" 1.0 0 -13345367 true "Plastic & glass stock" 1.0 0 -7500403 true "Not recyclable stock" 1.0 0 -6459832 true TEXTBOX 1076 532 1226 560 Blunderer people differentiate wrongly and randomly. 10 0.0 1 PLOT 460 163 760 313 Blue box weeks kilograms 0.0 10.0 0.0 100.0 true true PENS "R-Paper" 1.0 0 -13345367 true "Not R-Paper" 1.0 0 -6459832 true PLOT 460 316 760 503 Brown box weeks kilograms 0.0 10.0 0.0 100.0 true true PENS "Not recyclable" 1.0 0 -6459832 true "P-Not recycled" 1.0 0 -13345367 true "P&g-Not recycled" 1.0 0 -7500403 true PLOT 460 10 761 160 Gray box weeks kilograms 0.0 10.0 0.0 100.0 true true PENS "R-Plastic & glass" 1.0 0 -7500403 true "Not R-Plastic & glass" 1.0 0 -6459832 true TEXTBOX 1076 395 1226 423 Diligent people differentiate correctly. 10 0.0 1 TEXTBOX 1078 463 1228 491 Negligent people do not differentiate. 10 0.0 1 TEXTBOX 769 215 1194 253 Rubbish dump represents the amounts of rubbish after that the dustmen they have eliminated any \"intruders\". 10 0.0 1 MONITOR 763 550 863 595 % Diligents percentage-diligents 2 1 11 MONITOR 864 550 973 595 % Negligents percentage-negligents 2 1 11 MONITOR 974 550 1071 595 % Blunderers percentage-blunderers 2 1 11 MONITOR 669 379 760 420 Not recyclable Not-recyclable 2 1 10 BUTTON 249 10 335 48 Go once Go NIL 1 T OBSERVER NIL NIL NIL NIL PLOT 762 317 1070 548 Composition weeks percentage (%) 0.0 10.0 0.0 100.0 true true PENS "%Diligents" 1.0 0 -10899396 true "%Negligents" 1.0 0 -2674135 true "%Blunderers" 1.0 0 -1184463 true SWITCH 762 257 920 290 awareness-effect? awareness-effect? 0 1 -1000 TEXTBOX 923 263 1015 322 Resulting from environmental awareness campaigns. 10 0.0 1 TEXTBOX 466 526 544 600 represents the amounts of rubbish classified as paper. 10 0.0 1 TEXTBOX 553 525 644 586 represents the amounts of rubbish classified as not-recyclable. 10 0.0 1 TEXTBOX 467 511 617 529 Blu box 13 105.0 1 TEXTBOX 555 510 705 528 Brown box 13 35.0 1 TEXTBOX 657 524 747 582 represents the amounts of rubbish classified as plastic or glass. 10 0.0 1 TEXTBOX 657 509 807 527 Gray box 13 2.0 1 SWITCH 1004 281 1140 314 imitation-effect? imitation-effect? 0 1 -1000 TEXTBOX 1150 280 1240 349 Resulting from the social imitation phenomenon as means to change namely observational learning. 9 0.0 1 TEXTBOX 910 262 925 280 : 11 0.0 1 TEXTBOX 1131 287 1146 305 : 11 0.0 1 SWITCH 1003 237 1123 270 dustman-work? dustman-work? 0 1 -1000 MONITOR 1159 76 1222 113 Total kg Stock 2 1 9 MONITOR 663 61 761 98 Not R-Plastic & glass Not-recyclable_Plastic&Glass 2 1 9 MONITOR 663 93 761 130 R-Plastic & glass Recyclable_Plastic&Glass 2 1 9 MONITOR 1160 111 1222 148 Paper stock paper-stock 2 1 9 MONITOR 1160 145 1222 182 P&G stock plastic&glass-stock 2 1 9 MONITOR 1160 176 1222 213 Not rec stock not-recyclable-stock 2 1 9 MONITOR 682 214 760 251 Not R-Paper Not-recyclable_Paper 2 1 9 MONITOR 682 244 760 281 R-Paper Recyclable_Paper 2 1 9 MONITOR 669 410 760 447 P-Not recycled Paper_NotRecycled 2 1 9 MONITOR 669 438 760 475 P&g-Not recycled Plastic&Glass_NotRecycled 2 1 9 MONITOR 669 466 760 503 Total kg NotRecyclable 2 1 9 MONITOR 663 123 761 160 Total kg Plastic&Glass 2 1 9 MONITOR 682 276 760 313 Total kg Paper 2 1 9 MONITOR 986 401 1068 438 N° of Diligents (count turtles with [color = green]) 2 1 9 MONITOR 986 439 1068 476 N° of Negligents (count turtles with [color = red]) 2 1 9 MONITOR 986 477 1068 514 N° of Blunderers (count turtles with [color = yellow]) 2 1 9 MONITOR 1105 76 1161 113 Total kg Blue-box + Gray-box + Brown-box 2 1 9 MONITOR 1105 111 1161 148 BlueBox Blue-box 2 1 9 MONITOR 1105 145 1162 182 GrayBox Gray-box 2 1 9 MONITOR 1105 176 1162 213 BrownBox Brown-box 2 1 9 @#$#@#$#@ WHAT IS IT? ----------- The model simulates the garbage collection. The purpose of project is to analyse the social imitation phenomenon (observational learning) as mean to change the way to collect. Is imitative behavior enough to start a moral process? How many diligent people need to start this learning method? What policies are plausible and useful to begin the process? HOW IT WORKS ------------ The turtles are "houses." For each house, we set a random number of tenants between 0 and 6. Each house takes a different color depending on the breed of tenants: • diligents (differentiating rightly); • blunderers(differentiating wrongly and randomly); • negligents (not differentiating). If house has diligent tenants, it takes color green; if it has blunderer tenants, it takes color yellow; and if it has negligent tenants, it takes color red. Each turtle produces 3 types of rubbish per week: • plastic / glass, collecting in gray box, amounting <= that/to 1 kg per person per day • paper, collecting in blue box, amounting <= that/to 400 grams per person per day • undifferentiated, collecting in brown box, amounting <= that/to 300 grams per person per day. Blunderers classify as recyclable paper a share X of not recyclable rubbish, and as recyclable plastic/glass a share Y of not recyclable rubbish. We assume that X is between zero and 40% of not-recyclable rubbish and Y is between zero and 20% of not-recyclable rubbish. HOW TO USE IT ------------- Click the SETUP button to set up the houses. Click the GO button to start the simulation. Before starting the model, you can choose how many diligents, negligents and blunderers the world. Switching on "awareness-effect" and/or "imitation-effect" and/or "dustman-work" you can choose to start the environmental awareness campaign and/or social imitation and/or the work of dustmen. THINGS TO NOTICE ---------------- There are five windows. Three show what each common box contains: • Blue-Box is the paper basket, and contains two series: paper, by diligents and blunderers, and undifferentiated (classified recyclable paper by blunderers); • Gray-box is the plastic/glass basket, and contains two series: plastic, by diligent and blunderers, and undifferentiated (classified recyclable plastic and glass by blunderers); • Brown-box is the basket of non-recyclable rubbish and contains 3 series: paper and plastic not recycled by negligents, and undifferentiated (not recyclable) produced by everybody. The collection is virtual: every week rubbish flow to rubbish dump; so a plot shows the stocks of rubbish. The fifth plot shows the dynamic composition of the world. While the model is running each plot contains: • a monitor showing the total weekly amount of rubbish in that box • and so many monitors, how many plot series, showing the partial values. Monitors to the left (and to the right) of the "Rubbish dump plot" show total and partial amounts of rubbish with (without) dustman. EXTENDING THE MODEL ------------------- Would be interesting to extend the model allowing the possibility that within a "diligent community" could move some blunderers, or some negligents. Could be interesting a more accurately modelling of transition probabilities, allowing the probability of return to original state, after a positive development. An alternative approach could be to use the Swiss model to penalize nigligents and blunderers instead to remove imperfections. @#$#@#$#@ default true 0 Polygon -7500403 true true 150 5 40 250 150 205 260 250 airplane true 0 Polygon -7500403 true true 150 0 135 15 120 60 120 105 15 165 15 195 120 180 135 240 105 270 120 285 150 270 180 285 210 270 165 240 180 180 285 195 285 165 180 105 180 60 165 15 arrow true 0 Polygon -7500403 true true 150 0 0 150 105 150 105 293 195 293 195 150 300 150 box false 0 Polygon -7500403 true true 150 285 285 225 285 75 150 135 Polygon -7500403 true true 150 135 15 75 150 15 285 75 Polygon -7500403 true true 15 75 15 225 150 285 150 135 Line -16777216 false 150 285 150 135 Line -16777216 false 150 135 15 75 Line -16777216 false 150 135 285 75 bug true 0 Circle -7500403 true true 96 182 108 Circle -7500403 true true 110 127 80 Circle -7500403 true true 110 75 80 Line -7500403 true 150 100 80 30 Line -7500403 true 150 100 220 30 butterfly true 0 Polygon 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