turtles-own ; These are attributes owned by the agents [cooperate? ; Do they cooperate? retaliate? ; Do they punish individuals not like themselves in terms of cooperation? neighbors11 ; How many neighbors do they have who cooperate (1) and punish (1) neighbors01 ; How many neighbors do they have who don't cooperate (0) but do punish (1) neighbors10 ; etc..., these are updated each iteration of the model neighbors00 rations ; These are computed based how many resources they produce, acquire from neighbors, and lose by punishing or being punished future-cooperate ; These two variables are just markers so agents can change to be more like neighbors who are doing better than them future-retaliate ] to setup ca ; clear all ask patches ; ask patches to do the following [ sprout 1 [ ] ] ; each patch hatches an agent ask turtles ; ask the agents do the following [ ifelse start-random? ; if the start-random? switch is on, then allow individuals to take on random social roles [ set cooperate? random 2 ; set cooperate? to one of two settings randomly, either they do or do not cooperate ifelse allow-terrorists? ; if the allow-terrorists? switch is on, then allow individuals to become cooperater-punishing defectors [ set retaliate? random 2 ] [ ifelse cooperate? = 0 [ set retaliate? 0 ] [set retaliate? random 2 ] ] ; if not on, then non-cooperators can't retaliate (this is the classic altruistic punishment model) ] [ set cooperate? 1 set retaliate? 0 ] ; if the start-random? switch is off (see "ifelse" above), set shape "square" ; set the shape of all agents to a square mark ; call the method "mark" below ] end to mark ; this just colors and shapes individuals by their identity so they can easily be seen. if cooperate? = 1 and retaliate? = 0 [set color green set shape "square" ] if cooperate? = 1 and retaliate? = 1 [set color blue set shape "circle" ] if cooperate? = 0 and retaliate? = 0 [set color yellow set shape "square"] if cooperate? = 0 and retaliate? = 1 [set color red set shape "circle" ] end to go ; "go" calls methods for each iteration of the simulation social-adjustment ; probabilistically change identity based on quality of neighbors if mutate? [ mutate ] ; probabilistically change identity to random value update-turtles ; count neighbors by their identities divy-rations ; produce resources, then divide them up, and pay appropriate costs for production punish-offenders ; allow punishers to reduce resources of those they punish, and pay costs for punishment ask turtles [ mark ifelse labels? [set label precision rations 2 ] [ set label ""] ] ; identify individuals by color and shape do-plots ; calls the plot function below to plot interesting parameters end to mutate ask turtles [ if random 100 < 1 ; for each individual, if random value is less than mutation rate, then do following... [set cooperate? random 2 ; reset cooperate value ifelse allow-terrorists? ; see above (use "Find..." but to search for "allow-terrorists?" [ set retaliate? random 2 ] [ ifelse cooperate? = 0 [ set retaliate? 0 ] [set retaliate? random 2 ] ] ;show "mutated" ] ] end to divy-rations ask turtles [ ifelse cooperate? = 1 [ set rations (1 + neighbors11 + neighbors10) * bounty * 2 / 9 ] ; if you cooperate, you put your bounty in the pot [ set rations bounty + (neighbors11 + neighbors10) * bounty * 2 / 9 ] ; if you don't cooperate, you keep your bounty ;; set rations by cooperative neighbors ;; take what everyone throws in, double it, and then share it ifelse cooperate? = 1 [ ifelse retaliate? = 0 [ set rations rations - coop-cost ] ;; adjust rations by cooperation cost, if there is an extra cost for cooperating [set rations rations - cost-punishment * (neighbors01 + neighbors00) - base-cost-p]] ; police pay price to punish defectors, plus a base cost [ if retaliate? = 1 [set rations rations - cost-punishment * (neighbors11 + neighbors10) - base-cost-p]] ;; non-cooperators who punish all cooperators pay the price of punishing ] end to punish-offenders ask turtles [ if (cooperate? = 0 and retaliate? = 0) [ set rations rations - (neighbors11 ) * punishment ] ;; defectors are punished by police if (cooperate? = 0 and retaliate? = 1 ) [ set rations rations - (neighbors11) * punishment ] ;; droogs are punished by police if (cooperate? = 1 and retaliate? = 1) [ set rations rations - (neighbors01) * punishment ] ;; droogs punish police if (cooperate? = 1 and retaliate? = 0) [set rations rations - (neighbors01) * punishment ] ;;droogs punish cooperators (this could be made optional) ] end to social-adjustment locals [chosen-one change-p] ask turtles [ without-interruption [ set future-retaliate retaliate? ; I make this a global above, so agents don't get confused about which value belongs to whom set future-cooperate cooperate? set chosen-one one-of (turtles-on neighbors) ; pick a random neighbor if ( value-from chosen-one [rations] > rations ) [ ;; only change to neighbor if they're better and with probability p-change if ( random 100 ) / 100 < p-change [ set future-cooperate value-from chosen-one [cooperate?] ; set agents values to new values set future-retaliate value-from chosen-one [retaliate?] ;show "changed" ] ] ] ] ask turtles [ set cooperate? future-cooperate set retaliate? future-retaliate ] ;reassign values end to update-turtles ask turtles [ ;; in next two lines, we use "neighbors" to test the eight patches surrounding the current patch set neighbors11 count (turtles-on neighbors) ; this counts of neighbors with specific identities with [cooperate? = 1 and retaliate? = 1] set neighbors10 count (turtles-on neighbors) with [cooperate? = 1 and retaliate? = 0] set neighbors01 count (turtles-on neighbors) with [cooperate? = 0 and retaliate? = 1] set neighbors00 count (turtles-on neighbors) with [cooperate? = 0 and retaliate? = 0] ] end to do-plots set-current-plot "The Peoples" set-current-plot-pen "police; cooperators who punish" plot count turtles with [cooperate? = 1 and retaliate? = 1] set-current-plot-pen "terrorists; defectors who punish" plot count turtles with [cooperate? = 0 and retaliate? = 1] set-current-plot-pen "cooperators who don't punish" plot count turtles with [cooperate? = 1 and retaliate? = 0] set-current-plot-pen "passive-defectors" plot count turtles with [cooperate? = 0 and retaliate? = 0] set-current-plot "Terrorists" set-current-plot-pen "police" plot count turtles with [cooperate? = 1 and retaliate? = 1] set-current-plot-pen "terrorist" plot count turtles with [cooperate? = 0 and retaliate? = 1] set-current-plot "phase-police" plotxy count turtles with [retaliate? = 1 and cooperate? = 0] count turtles with [retaliate? = 1 and cooperate? = 1] set-current-plot "phase-cooperate" plotxy count turtles with [cooperate? = 1 and retaliate? = 0] count turtles with [cooperate? = 0 and retaliate? = 0 ] end @#$#@#$#@ GRAPHICS-WINDOW 201 10 590 420 10 10 18.05 1 10 1 1 1 0 1 1 1 -10 10 -10 10 CC-WINDOW 5 535 1115 630 Command Center 0 BUTTON 22 34 88 67 NIL setup\n NIL 1 T OBSERVER T NIL SLIDER 14 121 186 154 bounty bounty 0 100 50 1 1 NIL SLIDER 14 156 186 189 coop-cost coop-cost 0 100 0 1 1 NIL SLIDER 11 236 183 269 punishment punishment 0 200 200 1 1 NIL SLIDER 12 296 184 329 cost-punishment cost-punishment 0 10 0 1 1 NIL SLIDER 16 342 188 375 p-change p-change 0 100 1 1 1 NIL BUTTON 109 62 194 95 go go T 1 T OBSERVER T NIL PLOT 625 10 1229 244 The Peoples NIL NIL 0.0 10.0 0.0 10.0 true true PENS "police; cooperators who punish" 1.0 0 -13345367 true "cooperators who don't punish" 1.0 0 -10899396 true "terrorists; defectors who punish" 1.0 0 -2674135 true "passive-defectors" 1.0 0 -1184463 true BUTTON 107 11 188 44 go once go NIL 1 T OBSERVER T NIL SWITCH 52 429 155 462 labels? labels? 1 1 -1000 BUTTON 44 476 173 509 NIL set label rations NIL 1 T TURTLE T NIL BUTTON 40 522 178 555 NIL set label "" NIL 1 T TURTLE T NIL PLOT 630 264 940 414 Terrorists NIL NIL 0.0 10.0 0.0 10.0 true true PENS "terrorist" 1.0 0 -2674135 true "police" 1.0 0 -13345367 true SLIDER 10 197 182 230 base-cost-p base-cost-p 0 1 0.1 0.1 1 NIL PLOT 628 428 828 578 phase-police NIL NIL 0.0 10.0 0.0 10.0 true false PLOT 830 426 1030 576 phase-cooperate NIL NIL 0.0 10.0 0.0 10.0 true false SWITCH 258 459 447 492 allow-terrorists? allow-terrorists? 0 1 -1000 BUTTON 244 545 342 578 NIL no-display NIL 1 T OBSERVER T NIL BUTTON 351 544 426 577 NIL display NIL 1 T OBSERVER T NIL SWITCH 259 500 406 533 start-random? start-random? 0 1 -1000 SWITCH 52 389 156 422 mutate? mutate? 1 1 -1000 @#$#@#$#@ WHAT IS IT? ----------- A simple model of cooperators (altruists/), cooperators who punish non-cooperators (police), non-cooperators who punish cooperators (terrorists/droogs), and non-cooperators who don't punish anybody. HOW IT WORKS ------------ At each turn, all individuals throw their bounty into a pot (if they cooperate), where it is doubled, and then divided among neighbors (even if they are defectors and didn't cooperate). Police can then punish those who don't cooperate (but they pay a cost to do so) and terrorist/droogs can punish cooperators (but they also pay a cost to do so). Then there is a social-adjustment, where individuals can change to be like there neighbors if their neighbors did better than them in the last turn. HOW TO USE IT ------------- Adjust parameters to see what happens: 1. coop-cost = the cost of cooperating, it is subtracted from cooperators at each turn. 2. base-cost-p = the cost of being a policeman, substracted each turn 3. punishment = the amount subtracted from the punished. 4. cost-punishment = the amount subtracted from the punishers for each individual punished 5. p-change = the probability of changing to be like a neighbor who did better in the last turn. 6. mutate? = allows a few individuals to change to be something else, randomly (this is useful to turn on for a minute after the population goes to fixation--or you can press 'setup' and randomly mutate everyone). 7. allow-terrorists?? = will you allow non-cooperators to punish (i.e., will you allow terrorist/droogs in your population?) THINGS TO NOTICE ---------------- If there is no cost to punishing (cost-punishment = 0), then terrorists and defectors win often. Note what happens if you don't allow terrorists but have no cost to punishing; then cooperators always win. If there is a cost to punishing (cost-punishment > 0 ), then things are less predictable, and police can sometimes win. Try other things, like increasing the base-cost for punishing, the amount of punishment, and whether or not you allow terrorists. EXTENDING THE MODEL ------------------- You could try making it so that terrorists only punish the police (so they are strict retaliators); or you could make them hurt everyone (defectors as well). CREDITS AND REFERENCES ---------------------- This simulation was built by Thomas Hills (2006, updated in 2010). This simulation is discussed in more detail in "Building Ethical Agent Based Simulations: A Case Study of a Pathological Problem in Altruistic Punishment", presented at AlifeX ( the pdf can be found here: http://ethicalife.dynalias.org/abstracts.html ). Please email me with any bugs: thomhills@gmail.com. @#$#@#$#@ default true 0 Polygon -7500403 true true 150 5 40 250 150 205 260 250 link true 0 Line -7500403 true 150 0 150 300 link direction true 0 Line -7500403 true 150 150 30 225 Line -7500403 true 150 150 270 225 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 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