breed [ villages village ]

breed [ shops shop ]

breed [ extorters extorter ]

breed [ police police-officer ]

breed [ public consumer ]

globals [
;; global input parameters not manipulated via the interface
  max-shop-distance
  max-customers
  state-punishment-factor
  collaboration-probability
;; macro variable which can be accessed by police
  criminal-records
;; macro output variables
  confiscated
  total-money
  shopping-amount
  max-family-depth
  this-family-depth
  size-of-largest-family
  time-when-addio-pizzo-takes-over
  m-ass-a-p-shops
  m-ass-non-a-p
  m-ass-ext-act
  m-ass-ext-jail
  m-ass-ext-inact

  WC WO WNPV WP WS WE  ;; weights for salience calculation
  IDW                  ;; weights for calculating action probability from 
                       ;; individual drive and normative drive; IDW = 1 - NDW
  min-sal
  max-sal
  n-sal
  
  nonono
  nonoye
  noyeno
  noyeye
  yenono
  yenoye
  yeyeno
  yeyeye
  
  percentage-of-undetected-cases     ;; nonono
  percentage-of-unreported-cases     ;; no____
  percentage-of-completed-extortions ;; __ye__
  percentage-of-cases-with-arrest    ;; ____ye
  percentage-of-cases-with-punishment
  percentage-of-critical-consumers
  
  mean-shop-wealth-addio-pizzo
  mean-shop-wealth-non-addio-pizzo
  n-families 
  n-shops-non-addio-pizzo 
  n-shops-addio-pizzo 
  n-shops-still-paying 
  count-addio-pizzo-shopping
  count-non-addio-pizzo-shopping
  addio-pizzo-shopping-percentage

;; global variables only used to signal events of quantities between procedures  
  arrested?             ;; is only used to signal this fact between procedures
  convicted?            ;; is only used to signal this fact between procedures
  extortion-paid        ;; is only used to signal this fact 
  punishment-received   ;;  and the amount between procedures
;; global variables kept only for technical purposes
  ERROR-OCCURRED?
  message-id
  interface-filename
  logfile-name
  database-name
  extortion-database
;; means and standard deviations of norm saliences
  all-norms
  all-norm-types
  all-means
  all-sds   

]

;; the event board common to all agent types (except villages)
turtles-own [
  last-message-id
  my-norms
  my-norm-saliences
  my-compliances
  my-violations
  other-compliances
  other-violations
  punishments
  sanctions
  explicit-compliance-invocations
  explicit-violations
  individual-drive
  normative-drive
]

shops-own [
  shop-wealth
  old-wealth
  monthly-income
  addio-pizzo?
  bankrupt?
  current-customers
  date-of-recent-punishment
  amount-of-recent-punishment
  my-denunciation-propensity
  my-pay-extortion-propensity
]

extorters-own [
  extortion-radius
  extortion-level
  punishment-severity
  extorter-type
  extortion-now
  wealth
  forbidden-shops
  active?
  in-jail?
  was-in-jail?
  my-ruefulness
  pentito?
  time-of-jailing
  time-of-deactivation
  reactivation-time
  my-family
  role
  n-of-family-members
]

public-own [ 
  my-current-shop
  distance-to-my-current-shop
  private-wealth
  consumption-rate
  my-addio-pizzo-buy-propensity
]

police-own
[
  my-prosecution-propensity
]

patches-own [

]

directed-link-breed 
[
  reports-to-links reports-to-link
]

directed-link-breed
[
  levies-tribute-from-links levies-tribute-from-link
]

directed-link-breed 
[
  pay-links pay-link
]


directed-link-breed 
[
  threaten-links threaten-link
]

pay-links-own 
[ 
  
]

threaten-links-own [ 

]

;;;;;;;;;;;;;;;;;;;;;;;
;;
;; Setup Procedures
;;
;;;;;;;;;;;;;;;;;;;;;;;

to setup

  ;; (for this model to work with NetLogo's new plotting features,
  ;; __clear-all-and-reset-ticks should be replaced with clear-all at
  ;; the beginning of your setup procedure and reset-ticks at the end
  ;; of the procedure.)
  clear-all
  clear-output
;;  set saliences-and-propensities []
  set message-id 0
  set all-norms ( list "DO-NOT-SHOP-AT-EXTORTION-PAYER" "BUY-FROM-EXTORTION-PAYER" "DENOUNCE-EXTORTION" "DO-NOT-DENOUNCE" "ANXIETY-IS-JUSTIFIED" 
    "TRY-HARD-TO-IMPRISON" "DO-NOT-PAY-EXTORTION" "PAY-EXTORTION-AS-EVERYBODY-DOES" "DO-NOT-BETRAY-COLLEAGUES" "ABJURE-CRIME" )
  set all-norm-types ( list "LIBERAL"                   "TRADITIONAL"                       "LIBERAL"            "TRADITIONAL"     "TRADITIONAL"          
    "LIBERAL"              "LIBERAL"              "TRADITIONAL"                     "TRADITIONAL"              "LIBERAL" )
  set all-means n-values length all-norms [ 0 ] 
  set all-sds all-means 
  set max-sal (-1)
  set min-sal (2)
;; As the next two statements would not work for an applet they are preceded by a semicolon. Remove the semicolon if you want the interface and the database written to files (here and further down, search for "file")   
;   set interface-filename ( word "result_" rectify-date "_d" ( denunciation-propensity * 100 ) "_p" ( prosecution-propensity * 100 ) ".png" )
;   set database-name ( word "database" rectify-date ".csv" )
  set time-when-addio-pizzo-takes-over -1
  set ERROR-OCCURRED? false
  set total-money 0
;; this is for the version without norms and serves to search the parameter space of this version  
  if batch-version? and not norm-version?
  [
    set constant-random-seed? false
    set denunciation-propensity random-float-in-range 0.05 0.95
    set prosecution-propensity random-float-in-range 0.05 0.95
    set extortion-level-low random-float-in-range 10 50
    set extortion-level-high random-float-in-range extortion-level-low 75
    set punishment-severity-low random-float-in-range 10 50
    set punishment-severity-high random-float-in-range punishment-severity-low 75
    set ruefulness random-float-in-range 0.0 0.3
    set addio-pizzo-threshold random-float-in-range 0.05 0.95
  ]
;; these are only for the norm-version, initialisation for searching the parameter space of this model are planned but not yet implemented   

  set WC 0.99
  set WO 0.33
  set WNPV 0.66
  set WP 0.33
  set WS 0.99
  set WE 0.99
  set IDW 1 - NDW
  
;; this is the same for the version with norms and serve to search the parameter space of this version
  if batch-version? and norm-version?
  [
    set constant-random-seed? false
;; the following input parameters are initialised randomly for subsequent runs:
    set NDW random-float-in-range 0.3 0.7
    set DISCOUNT random-float-in-range 0.8 1.0
    set LOCAL random-float-in-range 2 10
    set BACKGROUND random-float-in-range -100 50 
    set benefit-for-victims random-float-in-range 100 200
    set conviction-probability random-float-in-range 0.1 0.8
    set extortion-level-low random-float-in-range 10 extortion-level-high
    set punishment-severity-low random-float-in-range 10 punishment-severity-high
  ]

;; If set to ON, the random seed has the same value in every run. Here it is set to 4711.
  if constant-random-seed? [ random-seed 4711 ] 
  
  set count-addio-pizzo-shopping 0
  set count-non-addio-pizzo-shopping 0
  create-villages initial-villages [ villages-setup ]
  setup-patches
  create-police initial-police [ police-setup ]
  create-shops initial-shops [ shops-setup ]
  set m-ass-non-a-p mean [ shop-wealth ] of shops 
  set mean-shop-wealth-non-addio-pizzo mean [ shop-wealth ] of shops with [ not addio-pizzo? and not bankrupt? ]
  create-extorters initial-extorters [ extorters-setup ]
  set m-ass-ext-act mean [ wealth ] of extorters
  create-public initial-public [ public-setup ]
  set-normative-predispositions
  set confiscated 0
  set shopping-amount initial-wealth
  set max-customers 2 * initial-public / initial-shops
  set state-punishment-factor 1.5
  set collaboration-probability 0.5
  
  set arrested? false
  set convicted? false
  set extortion-paid 0
  set extortion-database []
  let headline ( list "case-no" "time" "victim" "extorter" "denounced" "successful" "amount-paid" "punishment" "arrested" "convicted")
  set extortion-database lput headline extortion-database
  set criminal-records turtle-set nobody
  set percentage-of-critical-consumers arctan BACKGROUND

  
  reset-ticks
end

;; setup procedures for the different agent types follow
to villages-setup
  set color one-of [ 15 25 35 45 55 65 76 85 95 105 115 125 135 ]
  set shape "church"  
  set size 3
  move-to one-of patches with [ not any? other turtles-here ]
end

to public-setup
  set color white
  set shape "person"
  set size 0.5
  move-to one-of patches with [ not any? other turtles-here ]
  set my-current-shop min-one-of shops [ distance myself ]
  set private-wealth initial-wealth
  set consumption-rate random-float-in-range consumption-rate-low consumption-rate-high
  set last-message-id 0
  set my-norms ( list "DO-NOT-SHOP-AT-EXTORTION-PAYER" "BUY-FROM-EXTORTION-PAYER") 
  set my-norm-saliences n-values length my-norms [ 0.0 ] 
  set my-compliances n-values length my-norms [ 0 ]
  set my-violations n-values length my-norms [ 0 ]
  set other-compliances n-values length my-norms [ 0 ]
  set other-violations n-values length my-norms [ 0 ]
  set punishments n-values length my-norms [ 0 ]
  set sanctions n-values length my-norms [ 0 ]
  set explicit-compliance-invocations n-values length my-norms [ 0 ]
  set explicit-violations n-values length my-norms [ 0 ]
end

to police-setup
  set color green
  set shape "police"
  move-to one-of villages
  move-to one-of patches in-radius 2 with [not any? other turtles-here]
  set last-message-id 0
  set my-norms ( list "ANXIETY-IS-JUSTIFIED" "TRY-HARD-TO-IMPRISON" ) 
  set my-norm-saliences n-values length my-norms [ 0.0 ] 
  set my-compliances n-values length my-norms [ 0 ]
  set my-violations n-values length my-norms [ 0 ]
  set other-compliances n-values length my-norms [ 0 ]
  set other-violations n-values length my-norms [ 0 ]
  set punishments n-values length my-norms [ 0 ]
  set sanctions n-values length my-norms [ 0 ]
  set explicit-compliance-invocations n-values length my-norms [ 0 ]
  set explicit-violations n-values length my-norms [ 0 ]
end

to shops-setup ;; shops procedure
  set color blue
  set shape "house"
  move-to one-of villages
  move-to one-of patches in-radius ( world-width / sqrt count villages ) with [ not any? other turtles-here ]
  set addio-pizzo? false
  set bankrupt? false
  set shop-wealth random-float-in-range initial-wealth-min initial-wealth-max 
  set old-wealth shop-wealth
  if not norm-version? [ set my-denunciation-propensity denunciation-propensity ]
  set last-message-id 0
  set my-norms ( list "DENOUNCE-EXTORTION" "DO-NOT-DENOUNCE" "DO-NOT-PAY-EXTORTION" "PAY-EXTORTION-AS-EVERYBODY-DOES" ) 
  set my-norm-saliences n-values length my-norms [ 0.0 ] 
  set my-compliances n-values length my-norms [ 0 ]
  set my-violations n-values length my-norms [ 0 ]
  set other-compliances n-values length my-norms [ 0 ]
  set other-violations n-values length my-norms [ 0 ]
  set punishments n-values length my-norms [ 0 ]
  set sanctions n-values length my-norms [ 0 ]
  set explicit-compliance-invocations n-values length my-norms [ 0 ]
  set explicit-violations n-values length my-norms [ 0 ]
end

to extorters-setup
  set extortion-radius initial-extortion-radius
  set extorter-type "LL"
  set extortion-level extortion-level-low
  if ( random-float  1.0 > 0.5 ) 
  [ 
    set extortion-level extortion-level-high 
    set extorter-type replace-item 0 extorter-type "H" 
  ]
  set extortion-now extortion-level
  set punishment-severity punishment-severity-low
  if ( random-float  1.0 > 0.5 ) 
  [ 
    set punishment-severity punishment-severity-high 
    set extorter-type replace-item 1  extorter-type "H"
  ]
  set reactivation-time random-float-in-range reactivation-time-low reactivation-time-high
  set shape "person"
  set wealth 2000
  set forbidden-shops turtle-set nobody
  set my-family who
  set role "*"
  set active? true
  set in-jail? false
  set was-in-jail? false
  set pentito? false
  color-extorter
  move-to one-of villages
  move-to one-of patches in-radius 3 with [ not any? other turtles-here ]
  set last-message-id 0
  set my-norms ( list "DO-NOT-BETRAY-COLLEAGUES" "ABJURE-CRIME") 
  set my-norm-saliences n-values length my-norms [ 0.0 ]
  set my-compliances n-values length my-norms [ 0 ]
  set my-violations n-values length my-norms [ 0 ]
  set other-compliances n-values length my-norms [ 0 ]
  set other-violations n-values length my-norms [ 0 ]
  set punishments n-values length my-norms [ 0 ]
  set sanctions n-values length my-norms [ 0 ]
  set explicit-compliance-invocations n-values length my-norms [ 0 ]
  set explicit-violations n-values length my-norms [ 0 ]
  set my-ruefulness 0
end

to color-extorter
   set color 45
  if extorter-type = "LH" [ set color 25 ]
  if extorter-type = "HL" [ set color 15 ]
  if extorter-type = "HH" [ set color 125 ]
  if pentito? 
  [
    set color black
    set shape "bird"
  ] 
end

to set-normative-predispositions
  let LNP BACKGROUND
  let TNP 10
  ifelse LNP < 0
  [
    set LNP 0
    set TNP 0 - BACKGROUND 
  ]
  [
    set TNP 0
  ]

  ask ( turtle-set public shops extorters police )
  [  
    let my-norm-compliance-dispositions []
    let my-norm-violation-dispositions []
    foreach my-norms
    [
      let np position ? all-norms
      if item np all-norm-types = "LIBERAL" 
      [ 
        set my-norm-compliance-dispositions lput LNP my-norm-compliance-dispositions 
        set my-norm-violation-dispositions lput TNP my-norm-violation-dispositions 
      ]
      if item np all-norm-types = "TRADITIONAL"  
      [ 
        set my-norm-compliance-dispositions lput TNP my-norm-compliance-dispositions 
        set my-norm-violation-dispositions lput LNP my-norm-violation-dispositions 
      ]
    ]
    set my-compliances my-norm-compliance-dispositions
    set my-violations my-norm-violation-dispositions
    set other-compliances my-norm-compliance-dispositions
    set other-violations my-norm-violation-dispositions
    set punishments  my-norm-violation-dispositions
    set sanctions  my-norm-violation-dispositions
    set explicit-compliance-invocations my-norm-compliance-dispositions
    set explicit-violations  my-norm-violation-dispositions
  ]
end

to setup-patches
  ask patches
  [
    let nearest-village min-one-of villages [ distance myself ]
    set pcolor 3 + [ color ] of nearest-village
  ]
end

;;;;;;;;;;;;;;;;;;;;;;;;;;;
;;
;; Runtime Procedures
;;
;;;;;;;;;;;;;;;;;;;;;;;;;;;

to go
  
  ask shops [ set-shop-variables-for-next-period ]
  
  ask public [ go-shopping ]
  
  if not batch-version? [ set max-shop-distance max [ distance-to-my-current-shop ] of public ]
  
  ask shops [ set monthly-income shop-wealth - old-wealth ]
  
  ask extorters [ become-active ]

  
  ask shops with [ not bankrupt? ] [ wait-for-extorter ]

  ask shops with [ shop-wealth <= 0] [ close-down ]

  ask extorters [ consume ]

;; all money generated by the shops in this period is distributed among consumers
  set shopping-amount total-money / initial-public
  set total-money 0
;; which they now bring to their private accounts  
  ask public [ set private-wealth private-wealth + shopping-amount ]
  
;; the state compensates victims from its fund of confiscated money  
  compensate 
  
;; extorter hierarchies are analysed  
  report-hierarchies
  
;; several macro variables are prepared for periodic output
  prepare-output
  
  tick

  if ticks > maxticks or ERROR-OCCURRED?
  [ 
    prepare-final-output
    stop
  ]
end

;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;;
;; PROCEDURES USED BY ALL TYPES OF AGENTS (EXCEPT VILLAGES)
;;
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;

;; all kinds of agents calculate the salience of one norm when they need to make a decision which relates to this norm
;; they use these salience to calculate action propensities
to-report propensity-to [ action ]
  calculate-my-individual-drive-to action
  calculate-my-normative-drive-to action
  let a-prop ( IDW * individual-drive + NDW * normative-drive )
  report a-prop
end
  
to calculate-my-normative-drive-to [ action ]
  if action = "PAY"
  [
    calculate-a-salience "DO-NOT-PAY-EXTORTION"
    calculate-a-salience "PAY-EXTORTION-AS-EVERYBODY-DOES"
    let np-dont position "DO-NOT-PAY-EXTORTION" my-norms
    let np-do position "PAY-EXTORTION-AS-EVERYBODY-DOES" my-norms
    let normative-drive-to-pay item np-do my-norm-saliences
    let normative-drive-not-to-pay item np-dont my-norm-saliences
    ifelse normative-drive-to-pay > normative-drive-not-to-pay
    [
      set normative-drive normative-drive-to-pay
    ]
    [
      set normative-drive 1 - normative-drive-not-to-pay
    ]
  ]
  if action = "DENOUNCE"
  [
    calculate-a-salience "DO-NOT-DENOUNCE"
    calculate-a-salience "DENOUNCE-EXTORTION"
    let np-dont position "DO-NOT-DENOUNCE" my-norms
    let np-do position "DENOUNCE-EXTORTION" my-norms
    let normative-drive-to-denounce item np-do my-norm-saliences
    let normative-drive-not-to-denounce item np-dont my-norm-saliences
    ifelse normative-drive-to-denounce > normative-drive-not-to-denounce
    [
      set normative-drive normative-drive-to-denounce
    ]
    [
      set normative-drive 1 - normative-drive-not-to-denounce
    ]
  ]  
  if action = "BECOME PENTITO"
  [
    calculate-a-salience "ABJURE-CRIME"
    calculate-a-salience "DO-NOT-BETRAY-COLLEAGUES"
    let np-dont position "DO-NOT-BETRAY-COLLEAGUES" my-norms
    let np-do position "ABJURE-CRIME" my-norms
    let normative-drive-to-denounce item np-do my-norm-saliences
    let normative-drive-not-to-denounce item np-dont my-norm-saliences
    ifelse normative-drive-to-denounce > normative-drive-not-to-denounce
    [
      set normative-drive normative-drive-to-denounce
    ]
    [
      set normative-drive 1 - normative-drive-not-to-denounce
    ]
  ]
  if action = "PROSECUTE"
  [
    calculate-a-salience "TRY-HARD-TO-IMPRISON"
    calculate-a-salience "ANXIETY-IS-JUSTIFIED"
    let np-dont position "ANXIETY-IS-JUSTIFIED" my-norms
    let np-do position "TRY-HARD-TO-IMPRISON" my-norms
    let normative-drive-to-prosecute item np-do my-norm-saliences
    let normative-drive-not-to-prosecute item np-dont my-norm-saliences
    ifelse normative-drive-to-prosecute > normative-drive-not-to-prosecute
    [
      set normative-drive normative-drive-to-prosecute
    ]
    [
      set normative-drive 1 - normative-drive-not-to-prosecute
    ]
  ]
  if action = "SWITCH TO ADDIO-PIZZO SHOP"
  [
    calculate-a-salience "DO-NOT-SHOP-AT-EXTORTION-PAYER"
    calculate-a-salience "BUY-FROM-EXTORTION-PAYER"
    let np-dont position "BUY-FROM-EXTORTION-PAYER" my-norms
    let np-do position "DO-NOT-SHOP-AT-EXTORTION-PAYER"my-norms
    let normative-drive-to-switch item np-do my-norm-saliences
    let normative-drive-not-to-switch item np-dont my-norm-saliences
    ifelse normative-drive-to-switch > normative-drive-not-to-switch
    [
      set normative-drive normative-drive-to-switch
    ]
    [
      set normative-drive 1 - normative-drive-not-to-switch
    ]
  ]
end

to-report arctan [ argument ]
  report 1 - ( atan 1 argument ) / 180 
end

to calculate-my-individual-drive-to [ action ]
  if action = "PAY"
  [
    let benefit benefit-for-victims
    let extortion [ extortion-level ] of max-one-of out-pay-link-neighbors [ extortion-level ]
    let state-punishment extortion * state-punishment-factor
    let T-pay ( benefit - extortion ) - ( state-punishment * ( 1 - percentage-of-undetected-cases ) ) * ( 1 - collaboration-probability )
    let T-no-pay ( extortion - benefit ) - ( ( [ punishment-severity ] of max-one-of out-pay-link-neighbors [ extortion-level ] ) * percentage-of-cases-with-punishment )
    let individual-drive-to-pay arctan (0.01 *  T-pay ) 
    let individual-drive-not-to-pay arctan ( 0.01 * T-no-pay ) 
    set individual-drive individual-drive-to-pay / ( individual-drive-to-pay + individual-drive-not-to-pay )
  ]
  if action = "DENOUNCE"
  [
    set individual-drive ( 1 - percentage-of-undetected-cases ) * ( percentage-of-cases-with-punishment ) + percentage-of-critical-consumers
  ]
  if action = "PROSECUTE"
  [
    set individual-drive 0
  ]
  if action = "BECOME PENTITO"
  [
    set individual-drive percentage-of-cases-with-punishment
  ]
  if action = "SWITCH TO ADDIO-PIZZO SHOP"
  [
    set individual-drive 0.5 * [ shop-wealth ] of my-current-shop / mean-shop-wealth-non-addio-pizzo
    if individual-drive > 1 [ set individual-drive 1.0 ]
  ]
end

to calculate-a-salience [ a-norm ]
  let np position a-norm my-norms
  let C item np my-compliances
  let V item np my-violations
  let OC item np other-compliances
  let OV item np other-violations
  let P item np punishments
  let S item np sanctions
  let EC item np explicit-compliance-invocations
  let EV item np explicit-violations
  let numerator 0
  let denominator 0
  let OWN 0
  if C + V > 0 
  [ 
    set OWN ( C - V ) / ( C + V ) 
    set numerator numerator + WC
    set denominator denominator + 2 * WC
  ]
  let OBS 0
  if OC + OV > 0 
  [ 
    set OBS ( OC - OV ) / ( OC + OV ) 
    set numerator numerator + WO
    set denominator denominator + 2 * WO
  ]
  let NPV 0
  if OV + V > 0 
  [
    set NPV (OV + V - P - S ) 
    if NPV < 0 [ set NPV 0 ]
    set NPV NPV / ( OV + V)
    set numerator numerator + WNPV
    set denominator denominator + WNPV
  ]
  let maxPSOV P + S
  if OV + V > P + S [ set maxPSOV OV + V ]
  let P_max 0
  if maxPSOV > 0 
  [ 
    set P_max P / maxPSOV 
    set denominator denominator + WP
  ]
  let S_max 0
  if maxPSOV > 0 
  [ 
    set S_max S / maxPSOV 
    set denominator denominator + WS
]
  let ECEV 0
  if EC + EV > 0 
  [ 
    set ECEV ( EC - EV ) / ( EC + EV ) 
    set numerator numerator + WE
    set denominator denominator + 2 * WE
  ]
  let SAL 0
  if denominator > 0
  [
    set SAL ( ( numerator + OWN * WC + OBS * WO - NPV * WNPV + P_max * WP + S_max * WS + ECEV * WE ) / denominator )
  ]
  set my-norm-saliences replace-item np my-norm-saliences SAL 
  set n-sal n-sal + 1
  if SAL < min-sal [ set min-sal SAL ]
  if SAL > max-sal [ set max-sal SAL ]
end

;; PROCEDURES USED BY ALL KINDS OF AGENTS (EXCEPT VILLAGES)
;; all kinds of agents update their individual event board
to update-compliances [ a-norm ]
  if member? a-norm my-norms
  [
      let np position a-norm my-norms
      let old-value item np my-compliances
      set my-compliances replace-item np my-compliances ( old-value * DISCOUNT + 1 )
  ]
  ask ( turtle-set shops extorters public police ) in-radius LOCAL [ update-observed-compliances a-norm ]
end    
  
to update-violations [ a-norm ]
  if member? a-norm my-norms
  [
      let np position a-norm my-norms
      let old-value item np my-violations
      set my-violations replace-item np my-violations ( old-value * DISCOUNT + 1 )
  ]
  ask ( turtle-set shops extorters public police ) in-radius LOCAL [ update-observed-violations a-norm ]
end    

to update-observed-compliances [ a-norm ]
  if member? a-norm my-norms
  [
      let np position a-norm my-norms
      let old-value item np other-compliances
      set other-compliances replace-item np other-compliances ( old-value * DISCOUNT + 1 )
  ]
end    
  
to update-observed-violations [ a-norm ]
  if member? a-norm my-norms
  [
      let np position a-norm my-norms
      let old-value item np other-violations
      set other-violations replace-item np other-violations ( old-value * DISCOUNT + 1 )
  ]
end    

to update-punishments [ a-norm depth caller id ]
  if id = last-message-id [ stop ]
  if member? a-norm my-norms 
  [
    let np position a-norm my-norms
    let old-value item np punishments
    set punishments replace-item np punishments ( old-value * DISCOUNT + 1 )
  ]
  if depth = 0 
  [ ask ( turtle-set shops extorters public police ) in-radius LOCAL 
    [
      if member? a-norm my-norms 
      [ 
        update-punishments a-norm 1 myself message-id
        update-explicit-compliance-invocations a-norm 1 myself message-id
      ]
    ]
  ]
  set last-message-id id
end

to update-sanctions [ a-norm depth caller id ]
  if id = last-message-id [ stop ]
  if member? a-norm my-norms 
  [
    let np position a-norm my-norms
    let old-value item np sanctions
    set sanctions replace-item np sanctions ( old-value * DISCOUNT + 1 )
  ]
  if depth = 0 
  [ ask ( turtle-set shops extorters public police ) in-radius LOCAL 
    [ 
      if member? a-norm my-norms
      [
        update-sanctions a-norm 1 myself message-id
        update-explicit-compliance-invocations a-norm 1 myself message-id
      ]
    ]
  ]
  set last-message-id id
end

to update-explicit-compliance-invocations [ a-norm depth caller id ]
  if id = last-message-id [ stop ]
  if member? a-norm my-norms 
  [
    let np position a-norm my-norms
    let old-value item np explicit-compliance-invocations
    set explicit-compliance-invocations replace-item np explicit-compliance-invocations ( old-value * DISCOUNT + 1 )
  ]
  if depth = 0 
  [ ask ( turtle-set shops extorters public police ) in-radius LOCAL 
    [ 
      if member? a-norm my-norms
      [
        update-sanctions a-norm 1 myself message-id
        update-explicit-compliance-invocations a-norm 1 myself message-id
      ]
    ]
  ]
  set last-message-id id
end

to update-explicit-violations [ a-norm depth caller id ]
  if id = last-message-id [ stop ]
  if member? a-norm my-norms 
  [
    let np position a-norm my-norms
    let old-value item np explicit-violations
    set explicit-violations replace-item np explicit-violations ( old-value * DISCOUNT + 1 )
  ]
  if depth = 0 
  [
    let addressees ( turtle-set shops extorters public police ) with [ member? a-norm my-norms ] in-radius LOCAL
    ask addressees 
    [ 
      if member? a-norm my-norms
      [
        update-sanctions a-norm 1 myself message-id
        update-explicit-violations a-norm 1 myself message-id
      ]
    ]
  ]
  set last-message-id id
end

;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;;
;; PROCEDURES USED BY STATE AND POLICE (STATE IS THE GLOBAL LEVEL)
;;
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;

;; the state (the observer !!) compensates victims of extortion; the recipient receives invocations
;; of the three norms DO-NOT-PAY-EXTORTION, DENOUNCE-EXTORTION, and PAY-EXTORTION-AS-EVERYBODY-DOES
;; the latter being negative
to compensate
  while [ confiscated > initial-wealth-max and any? shops with [ amount-of-recent-punishment > 0 ] ]
  [
    ask min-one-of ( shops with [ amount-of-recent-punishment > 0 ] ) [ date-of-recent-punishment ] 
    [
      set confiscated confiscated - amount-of-recent-punishment
      set shop-wealth shop-wealth + amount-of-recent-punishment
      set message-id message-id + 1
      update-explicit-compliance-invocations "DO-NOT-PAY-EXTORTION" 0 self message-id
      update-explicit-compliance-invocations "DENOUNCE-EXTORTION" 0 self message-id 
      update-explicit-violations "PAY-EXTORTION-AS-EVERYBODY-DOES" 0 self message-id
      update-explicit-violations "DO-NOT-DENOUNCE" 0 self message-id
      set amount-of-recent-punishment 0
      set date-of-recent-punishment ticks + 5
      if bankrupt?
      [
        set bankrupt? false
        if random-float 1.0 < hide-denounce-propensity [ declare-membership-in-addio-pizzo ]
      ]
    ]
  ]
end

;; the court (only one, and  this one court is also represented by the observer) finds a criminal guilty with 
;; a certain probability and sends it to jail for some longer time and, if the criminal had been denounced
;; by the victim, the latter receives a remuneration which is 10 per cent of the money and other assets 
;; found with the criminal the other 90 per cent being transferred to compensation fund
;; all police receive invocations of the norm TRY-HARD-TO-IMPRISON
to convict [ criminals denouncer ]
  ask criminals 
  [ 
    update-explicit-compliance-invocations "ABJURE-CRIME" 0 self message-id
    if random-float 1.0 < conviction-probability
    [
      set in-jail? true
      ifelse denouncer != nobody
      [
        set confiscated confiscated + wealth * 0.9
        let remuneration wealth * 0.1
        ask denouncer [ set shop-wealth shop-wealth + remuneration ]
      ]
      [
        set confiscated confiscated + wealth
      ]
      set wealth 0
      set color grey
      set time-of-jailing ticks
      become-inactive
      update-compliances "TRY-HARD-TO-IMPRISON"
      update-violations "ANXIETY-IS-JUSTIFIE"
      ask police [ update-observed-compliances "TRY-HARD-TO-IMPRISON" ]
      ask police [ update-observed-violations "ANXIETY-IS-JUSTIFIED" ]
      set convicted? true
    ]
    ifelse norm-version?
    [
      set my-ruefulness propensity-to "BECOME PENTITO"
    ]
    [
      set my-ruefulness ruefulness
    ]
    if random-float 1.0 < my-ruefulness 
    [ 
      become-inactive
      become-rueful 
    ]
  ]
end

;; police prosecute extorters; the success rate depends on the salience of the norm "TRY-HARD-TO-IMPRISON", 
;; and all offenders are prosecuted and in case of success are kept in investigation custody, evenually a court
;; sends them to jail
;; unsuccessful police officers are criticised for having violated the TRY-HARD-TO-IMPRISON norm
;; the other police officers observe such a norm violation
;; in the case of success the opposite holds, of course
to prosecute [ offenders denouncer ]
  set criminal-records ( turtle-set criminal-records offenders )
  ifelse norm-version?
  [
    set my-prosecution-propensity propensity-to "PROSECUTE"
  ]
  [
    set my-prosecution-propensity prosecution-propensity ;; in the non-normative version the success rate is fixed
  ]
  ifelse random-float 1.0 < my-prosecution-propensity
  [ 
    set arrested? true
    update-compliances "TRY-HARD-TO-IMPRISON"
    update-violations "ANXIETY-IS-JUSTIFIED"
    ask police in-radius LOCAL 
    [ 
      update-observed-compliances "TRY-HARD-TO-IMPRISON" 
      update-explicit-violations "ANXIETY-IS-JUSTIFIED" 0 self message-id
    ]
    convict offenders denouncer
  ]
  [
    update-violations "TRY-HARD-TO-IMPRISON"
    update-compliances "ANXIETY-IS-JUSTIFIED"
    update-explicit-compliance-invocations "ANXIETY-IS-JUSTIFIED" 0 self message-id
    ask police in-radius LOCAL 
    [ 
      update-observed-violations "TRY-HARD-TO-IMPRISON" 
      update-observed-compliances "ANXIETY-IS-JUSTIFIED" 
      update-explicit-compliance-invocations "ANXIETY-IS-JUSTIFIED" 0 self message-id
    ]
    relieve-from denouncer offenders ;; after the police did not catch the extorter the latter has a chance to punish the victim
  ]
end

;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;;
;; PROCEDURES USED BY CONSUMERS (THE PUBLIC)
;;
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;

;; consumers decide to sanction a shop paying pizzo
to switch-to-addio-pizzo-shop
  set message-id message-id + 1
  let my-former-shop my-current-shop
  ask my-former-shop [ update-sanctions "DO-NOT-PAY-EXTORTION" 0 myself message-id ]
  ask my-former-shop [ update-explicit-violations "DO-NOT-PAY-EXTORTION" 0 myself message-id ]
  ask my-former-shop [ update-sanctions "DENOUNCE-EXTORTION" 0 myself message-id ]
  ask my-former-shop [ update-explicit-violations "DENOUNCE-EXTORTION" 0 myself message-id ]
  ask public in-radius LOCAL [ update-explicit-compliance-invocations "DO-NOT-SHOP-AT-EXTORTION-PAYER" 0 myself message-id ]
  ask public in-radius LOCAL [ update-observed-compliances "DO-NOT-SHOP-AT-EXTORTION-PAYER" ]
  ask public in-radius LOCAL [ update-explicit-violations "BUY-FROM-DENOUNCING-ENTREPRENEUR" 0 myself message-id ]
  ask public in-radius LOCAL [ update-observed-violations "BUY-FROM-DENOUNCING-ENTREPRENEUR" ]
  update-compliances "DO-NOT-SHOP-AT-EXTORTION-PAYER"
  let potential-shops shops with [ addio-pizzo? and not bankrupt? ]
  if count potential-shops > 0 [ set my-current-shop min-one-of potential-shops [ current-customers ] ]
end  

to support-pizzo-paying-shop
  set message-id message-id + 1
  ask shops in-radius LOCAL 
  [ 
    update-explicit-compliance-invocations "PAY-EXTORTION-AS-EVERYBODY-DOES" 0 self message-id 
    update-explicit-violations "DO-NOT-DENOUNCE" 0 self message-id 
  ] 
  ask public in-radius LOCAL [ update-explicit-violations "DO-NOT-SHOP-AT-EXTORTION-PAYER" 0 self message-id ]
  update-compliances "BUY-FROM-DENOUNCING-ENTREPRENEUR"
  ask public in-radius LOCAL [ update-observed-compliances "BUY-FROM-DENOUNCING-ENTREPRENEUR" ]
end

;; consumers buy
to buy-from [ a-shop ]
  let my-shopping-amount consumption-rate * shopping-amount
  ask a-shop [ set shop-wealth shop-wealth + my-shopping-amount ]
  set private-wealth private-wealth - my-shopping-amount
  ifelse [ addio-pizzo? ] of a-shop
  [
    set count-addio-pizzo-shopping count-addio-pizzo-shopping + 1
  ]
  [
    set count-non-addio-pizzo-shopping count-non-addio-pizzo-shopping + 1
  ]
end

;; consumers go shopping
to go-shopping
  let my-former-shop my-current-shop
  if my-current-shop != nobody
  [
    if [ bankrupt? or current-customers > max-customers ] of my-current-shop [ set my-current-shop nobody ]
  ]
  if my-current-shop = nobody 
  [
    let active-shops shops with [ not bankrupt? ] 
    set my-current-shop min-one-of active-shops [ current-customers ] 
  ]
  ifelse norm-version?
  [
    ifelse [ addio-pizzo? ] of my-current-shop 
    [
      update-violations "BUY-FROM-EXTORTION-PAYER"   
      update-compliances "DO-NOT-SHOP-AT-EXTORTION-PAYER" 
    ]
    [
      update-compliances "BUY-FROM-EXTORTION-PAYER"     
      update-violations "DO-NOT-SHOP-AT-EXTORTION-PAYER" 
    ]
    set my-addio-pizzo-buy-propensity propensity-to "SWITCH TO ADDIO-PIZZO SHOP"
  ]
  [
    set my-addio-pizzo-buy-propensity addio-pizzo-threshold
  ]
  if [ not addio-pizzo? ] of my-current-shop 
  [
    ifelse random-float 1.0 < my-addio-pizzo-buy-propensity 
    [ 
      switch-to-addio-pizzo-shop 
    ]
    [ 
      support-pizzo-paying-shop
    ]
  ]
  if [ not bankrupt? ] of my-current-shop  [ buy-from my-current-shop ]
  if not batch-version?
  [
    set distance-to-my-current-shop distance my-current-shop 
    set color scale-color black distance-to-my-current-shop max-shop-distance 1
  ]
end

;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;;
;; PROCEDURES USED BY SHOPS
;;
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;

;; at the beginning of each period shops set some variables
to set-shop-variables-for-next-period  
  set old-wealth shop-wealth 
  set current-customers count public with [ my-current-shop = myself ]
end

;; this procedure covers the shop owner's decision making and also reports extortion case
;; even those wich never become known to the police
to wait-for-extorter  
;;    buy supply for inventory and pay salaries
  let expenses-per-period fixed-cost-per-period + variable-cost-coefficient * monthly-income
  set shop-wealth shop-wealth - expenses-per-period  
  set total-money total-money + expenses-per-period   
;;    check whether extortion is requested
  if count my-out-pay-links > 0 
  [
;; an extortion is pending !! all the local variables are only used to add to the extortion database
    if count my-out-pay-links > 1 [ get-rid-of-other-extorters ]
    let my-current-extorter one-of out-pay-link-neighbors
    let this-victim [ who ] of self
    let this-extorter [ who ] of my-current-extorter   
    let this-denounced "no"
    let this-successful "no"  
    let this-amount-paid 0 
    let this-punishment 0
    let this-arrested "no"
    let this-convicted "no"
    ifelse norm-version?
    [
      set my-denunciation-propensity propensity-to "DENOUNCE" 
    ]
    [
      set my-denunciation-propensity denunciation-propensity
    ]
    ifelse ( random-float 1.0 < my-denunciation-propensity ) or addio-pizzo?
    [
      denounce
      ask police in-radius LOCAL [ update-explicit-compliance-invocations "TRY-HARD-TO-IMPRISON" 0 self message-id]
      set this-denounced "yes"
      if arrested? [ set this-arrested "yes" ]
      set arrested? false
      if convicted? [ set this-convicted "yes" ]
      set convicted? false
;;      decide-to-pay-or-not ;; paying pizzo when the extorter was denounced should occur only rarely
      if extortion-paid > 0 [ set this-successful "yes" ]
      set this-amount-paid extortion-paid
      set this-punishment punishment-received
      set extortion-paid 0
      set punishment-received 0
    ]
    [
      decide-to-pay-or-not ;; only when the shop decided not to denounce]
      if any? criminal-records
      [
        if member? my-current-extorter criminal-records
        [
          if any? police in-radius vision-range
          [
            ask one-of police in-radius vision-range [ prosecute my-current-extorter myself ] ;; that the victim "asks" a police officer to prosecute has only technical reasons 
            update-violations "DENOUNCE-EXTORTION"
            update-compliances "DO-NOT-DENOUNCE"
            update-punishments "DENOUNCE-EXTORTION" 0 self message-id
            set this-denounced "no"
            if extortion-paid > 0 [ set this-successful "yes" ]
            if arrested? [ set this-arrested "yes" ]
            set arrested? false
          ]
        ]
      ]
   ]
   let this-extortion ( list length extortion-database ticks this-victim this-extorter this-denounced this-successful this-amount-paid this-punishment this-arrested this-convicted )
   set extortion-database lput this-extortion extortion-database
 ]    
end

;; shops decide to resist extortion
;; they know that have violated the PAY-EXTORTION-AS-EVERYBODY-DOES norm 
;; the public and the shops receive invocation of the norms DO-NOT-SHOP-AT-EXTORTION-PAYER
;; and DO-NOT-PAY-EXTORTION, respectively
to declare-membership-in-addio-pizzo
  set addio-pizzo? true
  ask my-links [ die ]
  set message-id message-id + 1
  ask public in-radius LOCAL [ update-sanctions "DO-NOT-SHOP-AT-EXTORTION-PAYER" 0 myself message-id ]
  ask shops in-radius LOCAL [ update-sanctions "DO-NOT-PAY-EXTORTION" 0 myself message-id ]
  update-violations "PAY-EXTORTION-AS-EVERYBODY-DOES"
  set color red
end

;; shops denounce an extorter, in the non-norm version only when they have not paid pizzo; but one could think even here of having them denounce even after they have paid pizzo
to denounce
  let nearest-police-officer min-one-of police [ distance myself ]
  let my-extorters out-pay-link-neighbors
  ask nearest-police-officer [ prosecute my-extorters myself ]
  set message-id message-id + 1
  update-compliances  "DENOUNCE-EXTORTION"
  update-violations "DO_NOT_DENOUNCE"
  update-compliances "DO-NOT-PAY-EXTORTION"
  ask shops in-radius LOCAL [ update-observed-compliances "DENOUNCE-EXTORTION" ]
  ask shops in-radius LOCAL [ update-observed-violations "DO-NOT-DENOUNCE" ]
  ask shops in-radius LOCAL [ update-observed-compliances "DO-NOT-PAY-EXTORTION" ]
  ask police in-radius LOCAL [ update-explicit-compliance-invocations "TRY-HARD-TO-IMPRISON" 0 self message-id ]
  if not addio-pizzo? and random-float 1.0 < hide-denounce-propensity [ declare-membership-in-addio-pizzo ]
end

to decide-to-pay-or-not
  ifelse addio-pizzo? 
  [ 
    ask my-out-pay-links [ die ]
    ask my-in-threaten-links [ die ]
  ] ;; addio-pizzo members never pay
  [
    ifelse norm-version?
    [
      set my-pay-extortion-propensity propensity-to "PAY"
      ifelse ( random-float 1.0 < my-pay-extortion-propensity )  
      [
        pay-extortion 
        set message-id message-id + 1
        update-violations "DO-NOT-PAY-EXTORTION"
        update-compliances "PAY-EXTORTION-AS-EVERYBODY-DOES"
        ask shops in-radius LOCAL [ update-observed-violations "DO-NOT-PAY-EXTORTION" ]
      ]
      [
        ask my-out-pay-links [ die ]
        ask my-in-threaten-links [ die ]
        update-violations "PAY-EXTORTION-AS-EVERYBODY-DOES"
        ask shops in-radius LOCAL [ update-observed-violations "PAY-EXTORTION-AS-EVERYBODY-DOES" ] 
        update-compliances "DO-NOT-PAY-EXTORTION"
        ask shops in-radius LOCAL [ update-observed-violations "DO-NOT-PAY-EXTORTION" ]  
      ]
    ]
;; in the non-normative version not to denounce means to pay  
    [
      pay-extortion
    ]
  ]
end

;; competing extorters, shops decide to whom to pay; needs update 
to get-rid-of-other-extorters
  let my-extorter max-one-of out-pay-link-neighbors [ punishment-severity ]
  let other-extorters out-pay-link-neighbors  
  while [ count out-pay-link-neighbors > 1 ]
  [
    ask my-extorter [ protect-me-against myself other-extorters ]
    set other-extorters out-pay-link-neighbors
  ]
end  

;; shops pay extortion; they know that they have violated the DO-NOT-PAY-EXTORTION norm and that they have complied 
;; with the  PAY-EXTORTION-AS-EVERYBODY-DOES norm; the neighbouring shops observe this
to pay-extortion
  if not any? out-pay-link-neighbors [ stop ]
  let my-extorter max-one-of out-pay-link-neighbors [ punishment-severity ]
  let extortion-rate [ extortion-now ] of my-extorter
  let extortion monthly-income * extortion-rate / 100
  if extortion > shop-wealth [ set extortion shop-wealth ]
  set shop-wealth shop-wealth - extortion
  ask my-extorter [ set wealth wealth + extortion ]
  update-violations "DO-NOT-PAY-EXTORTION" 
  update-compliances "PAY-EXTORTION-AS-EVERYBODY-DOES"
  ask shops in-radius LOCAL [ update-observed-violations "DO-NOT-PAY-EXTORTION"]
  ask shops in-radius LOCAL [ update-observed-compliances  "PAY-EXTORTION-AS-EVERYBODY-DOES" ]
  if count out-pay-link-neighbors > 1
  [
    let other-extorters out-pay-link-neighbors  
    while [ count out-pay-link-neighbors > 1 ]
    [
      ask my-extorter [ protect-me-against myself other-extorters ]
      set other-extorters out-pay-link-neighbors
    ]
  ]
  set extortion-paid extortion
end

;; a shop which paid pizzo asks the successful extorter to protect it against rivals; a norm invocation needs to be added
;; this norm might be something like NEVER-EXTORT-SHOPS-PROTECTED-BY-ANOTHER-FAMILY, but this is not yet defined
to protect-me-against [ protection-seeker rivals ]
  if not any? other rivals 
  [ 
    stop 
  ]
  set my-family family 
  if my-family = -1 [ set ERROR-OCCURRED? true stop ]
  ask other rivals 
  [
    give-up protection-seeker
    subordinate-yourself-to myself
  ]
end

;; a shop is bankrupt and decides to give up; a norm invocation needs to be added
to give-up [ your-shop ]
  ask my-in-pay-links with [ other-end = your-shop ] 
  [ 
    die 
  ]
  ask my-out-threaten-links with [ other-end = your-shop ] 
  [ 
    die
  ]

  set forbidden-shops ( turtle-set forbidden-shops your-shop )
end

;; a shop closes
to close-down  
  ask out-pay-link-neighbors [ give-up myself ]
  set total-money total-money + shop-wealth
  set shop-wealth 0
  set bankrupt? true
  set color black
end

;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;;
;; PROCEDURES USED BY EXTORTERS
;;
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;

;; this procedure collects all activities of an extorter during one period
to become-active  
  if active? and not in-jail?
  [      
    if count my-in-pay-links = 0 or any? shops with [ count my-in-threaten-links = 0 ]
    [ 
      if not was-in-jail? [ set extortion-radius extortion-radius-extension * extortion-radius ]
      find-victims 
    ]
  ]
  if active? and not pentito? and wealth <= 0 ;; if an extorter has spent all its money for consumtive purposes it becomes inactive until its family helps it up
  [ 
    ask out-threaten-link-neighbors [ ask myself [ give-up self ] ]
    set active? false
    set color white
    set total-money total-money + wealth
    set wealth 0
    set time-of-deactivation ticks
  ]  
  if in-jail?
  [
    if ticks > time-of-jailing + time-in-jail 
    [
      set in-jail? false
      set was-in-jail? true
      color-extorter
      set extortion-radius initial-extortion-radius * 0.5
    ]
  ]
  if not active? and ticks - time-of-deactivation > reactivation-time
  [
    set active? true
    find-victims
    color-extorter
  ]
end

;; extorters try to find promising victims
to find-victims
  let allowed-shops shops in-radius extortion-radius with [ not addio-pizzo? and not bankrupt? ] 
  ask forbidden-shops
  [
    set allowed-shops other allowed-shops
  ]

  if random-float 1.0 < propensity-to-offend-addio-pizzo and 0 < count shops in-radius extortion-radius with [ addio-pizzo? and not bankrupt? ] 
  [
    let selected-anti-pizzo-shop one-of  shops in-radius extortion-radius with [ addio-pizzo? and not bankrupt? ] 
    set allowed-shops ( turtle-set selected-anti-pizzo-shop allowed-shops )
  ]
  create-pay-links-from allowed-shops [ set color blue set shape "arc" set hidden? not show-extortion-links? ]
  create-threaten-links-to allowed-shops [ set color red set shape "arc" set hidden? not show-extortion-links?]
  if random-float 1.0 < propensity-to-offend-addio-pizzo and count forbidden-shops > 5
  [
    let my-forbidden-shops turtle-set forbidden-shops
    ask forbidden-shops with [ addio-pizzo? ] [ set my-forbidden-shops other my-forbidden-shops ] ;; but-first remove-duplicates forbidden-shops
    set forbidden-shops turtle-set my-forbidden-shops
  ]
end  

;; extorters punish shops which have not paid pizzo; the shops know that they violated the PAY-EXTORTION-AS-EVERYBODY-DOES, other shops observe this 
;; and that a shop complied with the DO-NOT-PAY-EXTORTION norm
;; the punishment is public, thus the offender's name is inserted into the criminal records
to punish [ victim ]
  let punishment [ shop-wealth ] of victim * punishment-severity / 100
  ask victim 
  [ 
    if count out-pay-link-neighbors > 1 [ get-rid-of-other-extorters ]
    set shop-wealth shop-wealth - punishment 
    set date-of-recent-punishment ticks 
    update-violations "PAY-EXTORTION-AS-EVERYBODY-DOES"
    ask shops in-radius LOCAL [ update-observed-compliances "DO-NOT-PAY-EXTORTION"]
    ask shops in-radius LOCAL [ update-observed-violations  "PAY-EXTORTION-AS-EVERYBODY-DOES" ]
    ask victim [ ask one-of police in-radius vision-range [ prosecute out-pay-link-neighbors myself ] ]
    set amount-of-recent-punishment punishment
    set punishment-received punishment
  ]
  set wealth wealth + punishment
  set criminal-records ( turtle-set criminal-records myself )
end

;; extorters punish a shop which has denounced after police was not successful; the norm invocation are done in the punish procedure
to relieve-from [ victim offenders ]
  ask offenders
  [
    punish victim
  ]
end

;; an extorter spends its money once per period
to consume
  if active? and not in-jail?
  [      
    let c consumption-per-period
    if  c > wealth [ set c wealth ]
    set wealth wealth - c
    set total-money total-money + c
  ]
end  

;; for different reasons an extorter can become inactive (no money left, put to jail, pentito) 
to become-inactive
  ask my-out-threaten-links [ die ]
  ask my-in-pay-links [ die ]
end

;; an extorter decides to denounce colleagues (becomes a "pentito")
to become-rueful
  let my-accomplices ( turtle-set in-reports-to-link-neighbors in-levies-tribute-from-link-neighbors )
  if not any? my-accomplices [ stop ] ;; isolated extorters never become pentiti
  set criminal-records ( turtle-set criminal-records my-accomplices )
  ask my-accomplices [ update-explicit-compliance-invocations "ABJURE-CRIME" 0 self message-id ]
  ask my-accomplices [ update-observed-violations "DO-NOT-BETRAY-COLLEAGUES" ]
  set reactivation-time maxticks ;; this extorter will not become active again during this simulation run
;; now the pentito cuts all links to his neigbours in the family tree
  let my-boss one-of in-levies-tribute-from-link-neighbors
  let my-followers in-reports-to-link-neighbors
;; and gives up all current extortions
  ask my-in-pay-links [ die ]
  ask my-out-threaten-links [ die ]
  ask my-in-links [ die ]
  ask my-out-links [ die ]
  ask my-followers
  [
    ask my-out-reports-to-links with [ other-end = myself ] [ die ]
    if my-boss != nobody 
    [ 
      create-reports-to-link-to my-boss [ set color 52 set shape "my-arc" ]
      create-levies-tribute-from-link-from my-boss [ set color 25 set shape "my-arc" ]
    ]
  ]
  if my-boss != nobody
  [
    ask my-boss
    [
      ask my-out-levies-tribute-from-links with [ other-end = myself ] [ die ]
      create-levies-tribute-from-links-to my-followers  [ set color 25 set shape "my-arc" ]
    ]
  ]
  if not batch-version?
  [
    output-print " "
    output-print ( list who " leaves family " my-family ", boss was " my-boss )
    ifelse any? my-followers [ output-print ( list who "'s followers " [ who ] of my-followers " cut their links to " who ) ] [ output-print ( list who " had no followers" ) ] 
    ifelse my-boss != nobody [ output-print ( list [ who ] of my-boss " cut its links to " who ) ] [ output-print ( list who " had no followers" ) ]
    ifelse any? my-followers and my-boss != nobody 
    [ 
      output-print ( list [ who ] of my-followers " created links to " [ who ] of my-boss ) 
      output-print ( list [ who ] of my-boss " created links to " [ who ] of my-followers ) 
    ]  
    [ 
      output-print ( list " no consequences" ) 
    ]
  ]
  set pentito? true
  set color black 
  set shape "bird"
  right 90
  set my-family -1
end


;; an extorter joins a famliy when competitor turned out to be more powerful
to subordinate-yourself-to [ boss ]
  let boss-family 0
  set my-family family
  ask boss [ set boss-family family ]  
  if role = "*" and my-family != [ my-family ] of boss
  [
    create-reports-to-link-to boss [ set color 52 set shape "my-arc"]
    create-levies-tribute-from-link-from boss [ set color 25 set shape "my-arc" ]
    ifelse count in-reports-to-link-neighbors = 0 [ set role "-" ][ set role "+" ] 
  ]
end

;;;;;;;;;;;;;;
;;
;; Utilities
;;
;;;;;;;;;;;;;;  

;; extorters from hierarchies, here is how they are displayed
to report-sub-hierarchies [ indentation  ]
  ifelse count in-reports-to-link-neighbors = 0 
  [ 
  ]
  [ 
    let followers in-reports-to-link-neighbors
    output-type indentation 
    output-print [ who ] of followers 
    set indentation word indentation "..."
    set this-family-depth this-family-depth + 1
    ask followers 
    [ 
      if not batch-version?
      [
        output-type indentation 
        output-type who
        output-print role 
      ]
      report-sub-hierarchies indentation 
    ]
  ]
end


;; two recursive functions organising the redistribution of resources within a family
to collect-from-subordinates
  if count  in-reports-to-link-neighbors = 0 [ stop ]
  let accrual 0
  ask in-reports-to-link-neighbors
  [ 
    collect-from-subordinates 
    let payment wealth * solidarity
    set wealth wealth - payment
    set accrual accrual + payment
  ]
  set wealth wealth + accrual
end

to distribute-to-subordinates
  if count in-reports-to-link-neighbors = 0 [ stop ]
  let accrual 0
  let n-of-subordinates count in-reports-to-link-neighbors
  if n-of-subordinates > 0
  [
    let my-wealth wealth
    ask in-reports-to-link-neighbors
    [
      distribute-to-subordinates
      let payment my-wealth * solidarity / n-of-subordinates
      set wealth wealth + payment
      set accrual accrual - payment
    ]
  ]
  set wealth wealth + accrual
end  

;; this procedure serves two purposes: to document the family hierarchy and to redistribute money between the members of each family
to report-hierarchies
  let top-positions extorters with [ ( count out-reports-to-link-neighbors = 0 ) and ( count in-reports-to-link-neighbors > 0 ) ]
  if not batch-version?
  [
    output-print word "Current families at the end of period " ticks
    output-type "top-positions: " 
    ifelse any? top-positions [ output-print [ who ] of top-positions ] [ output-print "no top positions" ]
  ]
  let indentation "..."
  set this-family-depth 0
  set max-family-depth 0
  set size-of-largest-family 0
  ask top-positions
  [
    let accrual 0
    ask in-reports-to-link-neighbors 
    [ 
      collect-from-subordinates 
      let payment wealth * solidarity
      set wealth wealth - payment
      set accrual accrual + payment
    ]
    set wealth wealth + accrual
  ]
  ask top-positions
  [
    let accrual 0
    let n-of-subordinates count in-reports-to-link-neighbors
    if n-of-subordinates > 0
    [
      let my-wealth wealth
      ask in-reports-to-link-neighbors
      [
        distribute-to-subordinates
        let payment my-wealth * solidarity / n-of-subordinates
        set wealth wealth + payment
        set accrual accrual - payment
      ]
      set wealth wealth + accrual
    ]
  ]    
  ask top-positions 
  [
    if not batch-version?
    [
      output-type indentation 
      output-type who
      output-print role 
    ]
    report-sub-hierarchies indentation  
  ]
  ask extorters
  [
    ifelse role = "*"
    [ 
      set size 2 
      set n-of-family-members count extorters with [ family = [ my-family ] of myself ]
      if size-of-largest-family < n-of-family-members [ set size-of-largest-family n-of-family-members ]
    ]
    [ set size 1 ]
    if count out-reports-to-link-neighbors > 1 
    [ 
      show family
      show ( list "ERROR: in  " [ who ] of in-reports-to-link-neighbors ) 
      show ( list "ERROR: out " [ who ] of out-reports-to-link-neighbors )  
      set ERROR-OCCURRED? true
    ]
  ]
  if this-family-depth > max-family-depth [ set max-family-depth this-family-depth ]
end

;; reports to which family an extorter belongs
to-report family
  let result -1
  if count out-reports-to-link-neighbors > 1 
  [ 
    set ERROR-OCCURRED? true 
    show ( list "ERROR: family " [ who ] of out-reports-to-link-neighbors )
    ask out-reports-to-link-neighbors [ show ( list "ERROR: family " [ who ] of out-reports-to-link-neighbors ) ]
    report result 
  ]
  ifelse count out-reports-to-link-neighbors = 0
  [ set result who ]
  [
    let boss one-of out-reports-to-link-neighbors
    ask boss [ set result family ]
  ]
  report result
end

to prepare-output
  ifelse count shops with [ not addio-pizzo? and not bankrupt?] > 0 
  [ 
    set m-ass-non-a-p mean ( [ shop-wealth ] of shops with [ not addio-pizzo? and not bankrupt? ] ) 
  ]
  [
    set m-ass-non-a-p 0
  ]
  ifelse count shops with [ addio-pizzo? and not bankrupt? ] > 0 
  [ 
    set m-ass-a-p-shops  mean ( [ shop-wealth ] of shops with [ addio-pizzo? and not bankrupt? ] ) 
  ]
  [
    set m-ass-a-p-shops 0
  ]
  if time-when-addio-pizzo-takes-over < 0
  [
    if m-ass-a-p-shops > m-ass-non-a-p
    [
      set time-when-addio-pizzo-takes-over ticks
    ]
  ]

  ifelse count extorters with [ active? ] > 0 
  [ 
    set m-ass-ext-act mean [ wealth ] of extorters with [ active? ] 
  ]
  [
    set m-ass-ext-act 0
  ]

  ifelse count extorters with [ in-jail? ] > 0 
  [ 
    set m-ass-ext-jail mean [ wealth ] of extorters with [ in-jail? ] 
  ]
  [
    set m-ass-ext-jail 0
  ]

  ifelse count extorters with [ not active? ] > 0 
  [ 
    set m-ass-ext-inact mean [ wealth ] of extorters with [ not active? ] 
  ]
  [
    set m-ass-ext-inact 0
  ]
  
;; the following counts take only the past length-moving-average (or less) periods into account  
  let length-moving-average maxticks * 2 / 3
  set nonono length filter [ ticks - ( item 1 ? ) < length-moving-average and item 4 ? = "no" and item 5 ? = "no" and item 8 ? = "no" ] but-first extortion-database
  set nonoye length filter [ ticks - ( item 1 ? ) < length-moving-average and item 4 ? = "no" and item 5 ? = "no" and item 8 ? = "yes" ] but-first extortion-database
  set noyeno length filter [ ticks - ( item 1 ? ) < length-moving-average and item 4 ? = "no" and item 5 ? = "yes" and item 8 ? = "no" ] but-first extortion-database
  set noyeye length filter [ ticks - ( item 1 ? ) < length-moving-average and item 4 ? = "no" and item 5 ? = "yes" and item 8 ? = "yes" ] but-first extortion-database
  set yenono length filter [ ticks - ( item 1 ? ) < length-moving-average and item 4 ? = "yes" and item 5 ? = "no" and item 8 ? = "no" ] but-first extortion-database
  set yenoye length filter [ ticks - ( item 1 ? ) < length-moving-average and item 4 ? = "yes" and item 5 ? = "no" and item 8 ? = "yes" ] but-first extortion-database
  set yeyeno length filter [ ticks - ( item 1 ? ) < length-moving-average and item 4 ? = "yes" and item 5 ? = "yes" and item 8 ? = "no" ] but-first extortion-database
  set yeyeye length filter [ ticks - ( item 1 ? ) < length-moving-average and  item 4 ? = "yes" and item 5 ? = "yes" and item 8 ? = "yes" ] but-first extortion-database
  
  let n-extortions length filter [ ticks - ( item 1 ? ) < length-moving-average ] but-first extortion-database
  if n-extortions > 0
  [
    set percentage-of-undetected-cases nonono / n-extortions                                     ;; nonono
    set percentage-of-unreported-cases ( nonono + nonoye + noyeno + noyeye ) / n-extortions      ;; no____
    set percentage-of-completed-extortions ( noyeno + noyeye + yeyeno + yeyeye ) / n-extortions  ;; __ye__
    set percentage-of-cases-with-arrest ( nonoye + noyeye + yenoye + yeyeye ) / n-extortions     ;; ____ye
    set percentage-of-cases-with-punishment length filter [ ticks - ( item 1 ? ) < length-moving-average and item 7 ? > 0 ] but-first extortion-database / n-extortions
  ]
  set percentage-of-critical-consumers mean [ my-addio-pizzo-buy-propensity ] of public
end  
  
to prepare-final-output   
  let all-n n-values length all-norms [ 0 ]
  let all-sum all-n
  let all-sqsum all-n
  ask ( turtle-set extorters public police shops )
  [
    foreach all-norms 
    [
      let this-norm ?
      let np 0
      if member? this-norm my-norms 
      [ 
        set np position this-norm all-norms 
        let old-value item np all-n
        set all-n replace-item np all-n ( 1 + old-value )
        set old-value item np all-sum
        let my-np position this-norm my-norms 
        let new-value item my-np my-norm-saliences
        set all-sum replace-item np all-sum ( new-value + old-value )
        set old-value item np all-sqsum
        set all-sqsum replace-item np all-sqsum ( new-value * new-value + old-value ) 
      ] 
    ]     
  ]
  foreach all-norms 
  [
    let np position ? all-norms
    let this-n item np all-n
    if this-n > 0
    [
      set all-means replace-item np all-means ( ( item np all-sum ) / this-n )
      set all-sds replace-item np all-sds ( ( item np all-sqsum ) / this-n - ( item np all-means ) * ( item np all-means ) )
    ]  
  ] 
  ifelse count shops with [ addio-pizzo? and not bankrupt? ] > 0
  [
    set mean-shop-wealth-addio-pizzo mean [ shop-wealth ] of shops with [ addio-pizzo? and not bankrupt? ]
  ]
  [
    set mean-shop-wealth-addio-pizzo -1
  ]
  ifelse count shops with [ not addio-pizzo? and not bankrupt? ] > 0
  [
    set mean-shop-wealth-non-addio-pizzo mean [ shop-wealth ] of shops with [ not addio-pizzo? and not bankrupt? ]
  ]
  [
    set mean-shop-wealth-non-addio-pizzo -1
  ]
  set n-families count extorters with [ role = "*" and count out-levies-tribute-from-link-neighbors > 0 ]
  set n-shops-non-addio-pizzo count shops with [ not addio-pizzo? and not bankrupt? ]
  set n-shops-addio-pizzo count shops with [ addio-pizzo? and not bankrupt? ]
  set n-shops-still-paying count shops with [ count my-out-pay-links > 0 ]
  set all-means map [ word ? "," ] all-means
  set all-sds map [ word ? "," ] all-sds
  set addio-pizzo-shopping-percentage count-addio-pizzo-shopping / ( count-addio-pizzo-shopping + count-non-addio-pizzo-shopping )
;; As the following would not work in applets the following lines are preceded with a semicolon. Remove it if you want the interface and/ore database output
;  if export-interface? and behaviorspace-run-number = 0
;  [
;    export-interface interface-filename 
;    show word "interface exported to " interface-filename
;  ]
;  file-close
;  if not batch-version?
;  [
;    file-open database-name
;    foreach extortion-database
;    [
;      file-type item 0 ? ;; event
;      file-type ";"
;      file-type item 1 ? ;; time
;      file-type ";"
;      file-type item 2 ? ;; victim
;      file-type ";"
;      file-type item 3 ? ;; extorter
;      file-type ";"
;      file-type item 4 ? ;; denounced?
;      file-type ";"
;      file-type item 5 ? ;; completed?
;      file-type ";"
;      file-type item 6 ? ;; payment
;      file-type ";"
;      file-type item 7 ? ;; punishment
;      file-type ";"
;      file-type item 8 ? ;; arrested?
;      file-type ";"
;      file-print item 9 ? ;; convicted?
;    ]
;    file-close
;    show word "extortion database exported to " database-name
;  ]
  stop 
end  
  
to-report random-float-in-range [ low high ]
  report low + random-float ( high - low )
end

to-report sqr [ x ]
  report x * x
end

to-report rectify-date 
  let date-string date-and-time
  let colon position ":" date-string
  set date-string replace-item  colon date-string "-"
  set colon position ":" date-string
  set date-string replace-item  colon date-string "-"
  set colon position "." date-string
  set date-string replace-item  colon date-string "-"  
  let year substring date-string 23 27
  let month substring date-string 19 22
  if month = "Okt" [ set month "Oct" ]
  if month = "Dez" [ set month "Dec" ]
  if month = "Mär" [ set month "Mar" ]
  if month = "Mai" [ set month "May" ]
  let day substring date-string 16 18
  let AMPM substring date-string 13 15
  let hour substring date-string 0 2
  let minsec substring date-string 2 12
  let month-number ( 1 + ( position month ( list "Jan" "Feb" "Mar" "Apr" "May" "Jun" "Jul" "Aug" "Sep" "Oct" "Nov" "Dec" ) ) )
  ifelse month-number < 10 [ set month ( word "0" month-number ) ] [ set month ( word month-number ) ]
  let num-hour read-from-string hour  
  if AMPM = "PM" [ set hour ( word ( num-hour + 12 ) ) ]
  set date-string ( word year "-" month "-" day " " hour minsec )
  report date-string
end
@#$#@#$#@
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ticks
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BUTTON
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setup
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T
OBSERVER
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BUTTON
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go
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OBSERVER
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BUTTON
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go once
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SWITCH
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constant-random-seed?
constant-random-seed?
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TEXTBOX
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World
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SLIDER
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TEXTBOX
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Shops' parameters:
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SLIDER
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Police's parameters:
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PLOT
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Mean assets of extorters
NIL
NIL
0.0
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0.0
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false
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"" ""
PENS
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"in jail" 1.0 0 -13210332 true "" "plot m-ass-ext-jail"
"inactive" 1.0 0 -16777216 true "" "plot m-ass-ext-inact"

PLOT
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Mean assets of targets
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0.0
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"" ""
PENS
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Extorters' parameters
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SLIDER
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initial-villages
initial-villages
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PLOT
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1480
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Number of extorters
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NIL
0.0
10.0
0.0
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true
true
"" ""
PENS
"inactive" 1.0 0 -4539718 true "" "plot count extorters with [ not active? ]"
"in jail" 1.0 0 -13210332 true "" "plot count extorters with [ in-jail? ]"
"active" 1.0 0 -2674135 true "" "plot count extorters with [ active? and not in-jail? ]"
"pentito" 1.0 0 -11221820 true "" "plot count extorters with [ pentito? ]"

SLIDER
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490
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initial-public
initial-public
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HORIZONTAL

TEXTBOX
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Consumers' parameters
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0.0
1

SLIDER
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addio-pizzo-threshold
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0.05
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NIL
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SWITCH
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325
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show-extortion-links?
show-extortion-links?
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OUTPUT
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8

PLOT
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585
1305
735
Families
NIL
NIL
0.0
10.0
0.0
10.0
true
true
"" ""
PENS
"number" 1.0 0 -16777216 true "" "plot count extorters with [ role = \"*\" and count out-levies-tribute-from-link-neighbors > 0 ]"
"max depth" 1.0 0 -8630108 true "" "plot max-family-depth"
"max size" 1.0 0 -5825686 true "" "plot size-of-largest-family"
"isolated" 1.0 0 -7500403 true "" "plot count extorters with [ ( count my-in-levies-tribute-from-links = 0 ) and active? and not in-jail? ]"

PLOT
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435
1780
585
Current distribution of assets
NIL
NIL
0.0
10.0
0.0
10.0
true
true
"" ""
PENS
"addio-pizzo" 1.0 0 -2674135 true "" "plot sum [ shop-wealth ] of  shops with [ addio-pizzo? and not bankrupt? ]"
"pizzo payers" 1.0 0 -13345367 true "" "plot sum [ shop-wealth ] of shops with [ not addio-pizzo? and not bankrupt? ]"
"active extorters" 1.0 0 -955883 true "" "plot sum [ wealth ] of extorters with [ active? and not in-jail? ]"
"inactive extorters" 1.0 0 -11221820 true "" "plot sum [ wealth ] of extorters with [ not active? and not in-jail? ]"
"confiscated" 1.0 0 -16777216 true "" "plot confiscated"
"private" 1.0 0 -13840069 true "" "plot sum [ private-wealth ] of public"

MONITOR
380
535
500
580
remaining addio-pizzo
count shops with [ not bankrupt? and addio-pizzo? ]
17
1
11

MONITOR
500
535
625
580
remaining pizzo payers
count shops with [ not addio-pizzo? and not bankrupt? ]
17
1
11

MONITOR
380
625
500
670
failed addio-pizzo
count shops with [ addio-pizzo? and bankrupt? ]
17
1
11

MONITOR
500
625
625
670
failed pizzo payers
count shops with [ not addio-pizzo? and bankrupt? ]
17
1
11

MONITOR
630
535
732
580
active extorters
count extorters with [ active? ]
17
1
11

MONITOR
735
535
875
580
extorters in jail
count extorters with [ in-jail? ]
17
1
11

MONITOR
630
580
732
625
retired extorters
count extorters with [ not active? ]
17
1
11

MONITOR
735
580
875
625
extorters previously in jail
count extorters with [ was-in-jail? ]
17
1
11

SLIDER
175
365
370
398
propensity-to-offend-addio-pizzo
propensity-to-offend-addio-pizzo
0
1
0
0.1
1
NIL
HORIZONTAL

SLIDER
5
365
160
398
reactivation-time-low
reactivation-time-low
0
20
5
1
1
NIL
HORIZONTAL

MONITOR
380
580
500
625
currently paying
count shops with [ addio-pizzo? and count my-out-pay-links > 0 ]
17
1
11

MONITOR
500
580
625
625
currently paying
count shops with [ not addio-pizzo? and count my-out-pay-links > 0 ]
17
1
11

SLIDER
5
400
160
433
reactivation-time-high
reactivation-time-high
0
20
10
1
1
NIL
HORIZONTAL

MONITOR
380
680
460
725
total wealth
sum [ wealth ] of extorters + sum [ shop-wealth ] of shops + confiscated + total-money + sum [ private-wealth ] of public
2
1
11

MONITOR
470
680
567
725
wealth of shops
sum [ shop-wealth ] of shops
2
1
11

MONITOR
570
680
655
725
wealth of extorters
sum [ wealth ] of extorters
2
1
11

MONITOR
660
680
720
725
confiscated
confiscated
2
1
11

SLIDER
10
105
190
138
fixed-cost-per-period
fixed-cost-per-period
0
500
300
100
1
NIL
HORIZONTAL

PLOT
895
435
1100
585
Number of shops
NIL
NIL
0.0
10.0
0.0
10.0
true
true
"" ""
PENS
"pizzo-payers" 1.0 0 -13345367 true "" "plot count shops with [ not addio-pizzo? and not bankrupt? ]"
"addio-pizzo" 1.0 0 -2674135 true "" "plot count shops with [ addio-pizzo? and not bankrupt? ]"
"failed shops" 1.0 0 -7500403 true "" "plot count shops with [  bankrupt? ]"

SLIDER
185
530
365
563
initial-wealth
initial-wealth
0
1000
200
50
1
NIL
HORIZONTAL

SLIDER
10
140
192
173
variable-cost-coefficient
variable-cost-coefficient
0
1
0.9
0.1
1
NIL
HORIZONTAL

MONITOR
730
680
780
725
private
sum [ private-wealth ] of public
17
1
11

SLIDER
185
565
365
598
consumption-rate-low
consumption-rate-low
0.0
1
0.9
0.1
1
NIL
HORIZONTAL

SLIDER
185
600
365
633
consumption-rate-high
consumption-rate-high
0.0
1
1
0.1
1
NIL
HORIZONTAL

SWITCH
200
790
325
823
batch-version?
batch-version?
1
1
-1000

SWITCH
170
700
325
733
export-interface?
export-interface?
1
1
-1000

SWITCH
360
790
485
823
norm-version?
norm-version?
0
1
-1000

SLIDER
515
760
687
793
DISCOUNT
DISCOUNT
0
1
0.9
0.1
1
NIL
HORIZONTAL

SLIDER
695
760
867
793
LOCAL
LOCAL
0
20
8
1
1
NIL
HORIZONTAL

SLIDER
515
790
687
823
NDW
NDW
0
1
0.55
0.05
1
NIL
HORIZONTAL

MONITOR
1125
765
1257
810
Messages exchanged
message-id
17
1
11

PLOT
1140
60
1300
180
DO NOT PAY EXTORTION
NIL
NIL
0.0
10.0
0.0
10.0
true
false
"set-plot-pen-mode 1\nset-plot-x-range 0.0 1.05\nset-plot-pen-color black\nset-plot-pen-interval 0.05\nset-plot-y-range 0 initial-shops" ""
PENS
"default" 1.0 0 -16777216 true "" "histogram [ item 2 my-norm-saliences ] of shops"

PLOT
980
60
1140
180
DENOUNCE
NIL
NIL
0.0
10.0
0.0
10.0
true
false
"set-plot-pen-mode 1\nset-plot-x-range 0.0 1.05\nset-plot-pen-color black\nset-plot-pen-interval 0.05" ""
PENS
"default" 0.05 1 -16777216 true "" "histogram [ item 0 my-norm-saliences ] of shops"

MONITOR
965
765
1120
810
n-sal min-sal max-sal
( list n-sal precision min-sal 3 precision max-sal 3 )
17
1
11

PLOT
1300
60
1460
180
DO NOT SHOP AT EXTORTION PAYER
NIL
NIL
0.0
10.0
0.0
10.0
true
false
"set-plot-pen-mode 1\nset-plot-x-range 0.0 1.05\nset-plot-pen-color black\nset-plot-pen-interval 0.05" ""
PENS
"default" 1.0 0 -1 true "" "histogram [ item 0 my-norm-saliences ] of public"

PLOT
1140
180
1300
300
PAY EXTORTION AS EVERYBODY DOES
NIL
NIL
0.0
10.0
0.0
10.0
true
false
"set-plot-pen-mode 1\nset-plot-x-range 0.0 1.05\nset-plot-pen-color black\nset-plot-pen-interval 0.05" ""
PENS
"default" 1.0 0 -16777216 true "" "histogram [ item 3 my-norm-saliences ] of shops"

PLOT
1620
60
1780
180
TRY HARD TO IMPRISON
NIL
NIL
0.0
10.0
0.0
10.0
true
false
"set-plot-pen-mode 1\nset-plot-x-range 0.0 1.05\nset-plot-pen-color black\nset-plot-pen-interval 0.05" ""
PENS
"default" 1.0 0 -16777216 true "" "histogram [ item 1 my-norm-saliences ] of police"

TEXTBOX
370
765
520
783
Norm oriented version\n
11
0.0
1

TEXTBOX
15
190
205
208
irrelevant in the norm version
11
125.0
1

TEXTBOX
95
635
295
653
irrelevant in the norm version
11
125.0
1

SLIDER
5
565
177
598
vision-range
vision-range
0
100
100
10
1
NIL
HORIZONTAL

SLIDER
5
735
160
768
maxticks
maxticks
0
100
100
5
1
NIL
HORIZONTAL

SLIDER
5
600
177
633
conviction-probability
conviction-probability
0
1
0.340175125979706
0.05
1
NIL
HORIZONTAL

PLOT
895
585
1100
735
Extortion types per cent
NIL
NIL
0.0
1.0
0.0
1.0
true
true
"" ""
PENS
"undetected" 1.0 0 -16777216 true "" "plot percentage-of-undetected-cases"
"undenounced" 1.0 0 -7500403 true "" "plot percentage-of-unreported-cases"
"completed" 1.0 0 -955883 true "" "plot percentage-of-completed-extortions"
"arrested" 1.0 0 -13210332 true "" "plot percentage-of-cases-with-arrest"
"punished" 1.0 0 -2674135 true "" "plot percentage-of-cases-with-punishment"

SLIDER
175
435
370
468
ruefulness
ruefulness
0
1
0.1
0.05
1
NIL
HORIZONTAL

SLIDER
5
435
160
468
solidarity
solidarity
0
1
0.35
0.05
1
NIL
HORIZONTAL

SLIDER
695
790
867
823
BACKGROUND
BACKGROUND
-100
100
-70
10
1
NIL
HORIZONTAL

PLOT
980
300
1140
420
denunciation
NIL
NIL
0.0
1.0
0.0
10.0
true
false
"set-plot-pen-mode 1\nset-plot-x-range 0.0 1.05\nset-plot-pen-color black\nset-plot-pen-interval 0.05" ""
PENS
"default" 0.05 1 -16777216 true "" "histogram [ my-denunciation-propensity ] of shops"

PLOT
1140
300
1300
420
pay extortion
NIL
NIL
0.0
1.0
0.0
10.0
true
false
"set-plot-pen-mode 1\nset-plot-x-range 0.0 1.05\nset-plot-pen-color black\nset-plot-pen-interval 0.05" ""
PENS
"default" 1.0 1 -16777216 true "" "histogram [ my-pay-extortion-propensity ] of shops"

PLOT
1620
300
1780
420
prosecute
NIL
NIL
0.0
1.0
0.0
10.0
true
false
"set-plot-pen-mode 1\nset-plot-x-range 0.0 1.05\nset-plot-pen-color black\nset-plot-pen-interval 0.05" ""
PENS
"default" 1.0 1 -16777216 true "" "histogram [ my-prosecution-propensity ] of police"

PLOT
1300
300
1460
420
buy from addio-pizzo
NIL
NIL
0.0
1.0
0.0
10.0
true
false
"set-plot-pen-mode 1\nset-plot-x-range 0.0 1.05\nset-plot-pen-color black\nset-plot-pen-interval 0.05" ""
PENS
"default" 1.0 1 -1 true "" "histogram [ my-addio-pizzo-buy-propensity ] of public"

SLIDER
175
400
370
433
benefit-for-victims
benefit-for-victims
0
200
180
5
1
%
HORIZONTAL

PLOT
980
180
1140
300
DO NOT DENOUNCE
NIL
NIL
0.0
10.0
0.0
10.0
true
false
"set-plot-pen-mode 1\nset-plot-x-range 0.0 1.05\nset-plot-pen-color black\nset-plot-pen-interval 0.05\nset-plot-y-range 0 initial-shops" ""
PENS
"default" 1.0 0 -16777216 true "" "histogram [ item 1 my-norm-saliences ] of shops"

SLIDER
210
140
375
173
hide-denounce-propensity
hide-denounce-propensity
0
1
0.2
0.05
1
NIL
HORIZONTAL

TEXTBOX
1025
10
1320
28
Action related saliences and propensities
11
0.0
1

TEXTBOX
1005
40
1155
58
denounce
11
0.0
1

TEXTBOX
1155
40
1305
58
pay extortion
11
0.0
1

TEXTBOX
1315
40
1465
58
select addio-pizzo shop
11
0.0
1

TEXTBOX
1650
40
1800
58
prosecute
11
0.0
1

TEXTBOX
890
100
1040
126
salience\ncivic norm
11
0.0
1

TEXTBOX
890
225
1040
251
salience\ntraditional norm
11
0.0
1

TEXTBOX
890
335
975
375
action propensity
11
0.0
1

PLOT
1460
60
1620
180
ABJURE CRIME
NIL
NIL
0.0
10.0
0.0
10.0
true
false
"set-plot-pen-mode 1\nset-plot-x-range 0.0 1.05\nset-plot-pen-color black\nset-plot-pen-interval 0.05" ""
PENS
"default" 1.0 0 -1 true "" "histogram [ item 1 my-norm-saliences ] of extorters"

TEXTBOX
1475
40
1625
58
become pentito
11
0.0
1

PLOT
1460
180
1620
300
DO NOT BETRAY
NIL
NIL
0.0
10.0
0.0
10.0
true
false
"set-plot-pen-mode 1\nset-plot-x-range 0.0 1.05\nset-plot-pen-color black\nset-plot-pen-interval 0.05" ""
PENS
"default" 1.0 0 -1 true "" "histogram [ item 0 my-norm-saliences ] of extorters"

PLOT
1460
300
1620
420
become pentito
NIL
NIL
0.0
1.0
0.0
10.0
true
false
"" "set-plot-pen-mode 1\nset-plot-x-range 0.0 1.05\nset-plot-pen-color black\nset-plot-pen-interval 0.05"
PENS
"default" 1.0 0 -1 true "" "histogram [ my-ruefulness ] of extorters"

PLOT
1620
180
1780
300
ANXIETY IS JUSTIFIED
NIL
NIL
0.0
10.0
0.0
10.0
true
false
"set-plot-pen-mode 1\nset-plot-x-range 0.0 1.05\nset-plot-pen-color black\nset-plot-pen-interval 0.05" ""
PENS
"default" 1.0 0 -16777216 true "" "histogram [ item 0 my-norm-saliences ] of police"

PLOT
1300
180
1460
300
BUY FROM DENOUNCING ENTREPRENEUR
NIL
NIL
0.0
10.0
0.0
10.0
true
false
"set-plot-pen-mode 1\nset-plot-x-range 0.0 1.05\nset-plot-pen-color black\nset-plot-pen-interval 0.05" ""
PENS
"default" 1.0 0 -16777216 true "" "histogram [ item 1 my-norm-saliences ] of public"

@#$#@#$#@
##  WHAT IS IT?

This model is an attempt at modelling the behaviour of extorters, their victims and
police in the context of the GLODERS project. It uses some but not all of the features described by Luis Gustavo Nardin, Giulia Andrighetto, Rosaria Conte, Mario Paolucci in their IntERS model (http://www.gloders.eu/images/Deliverables/GLODERS_D3-1.pdf) and extends it with territoriality and some more features as discussed during GLODERS project meetings.

Whereas an earlier version (http://ccl.northwestern.edu/netlogo/models/community/ARDERS) was mainly devoted to analyse the systemic effects of the behaviour of the agents, whose decision making processes are only modelled rather crudely, this version includes the registration of events by most groups of agents, the identification of these events as relevant for one of the norms which partly govern the agent behaviour as well as the calculation of the salience of these norms for future actions of the agents. This salience is converted into a propensity to take an action by either abiding by the respective norm or violating it.

##  HOW IT WORKS

The world contains several villages (shape: church) in which several enterprises (shape: house) exist which can fall victim to extortion. Extorters (shape: person) can approach 
their targets first in their immediate vicinity, if they do not find any more potential victims in their immediate vicinity they extend this vicinity. 

**Normative board**
In the norm version, agents of all types have a normative board, in which norms are represented, and a mechanism with which they can remember events and norm invocations, and they can calculate the salience of the respective norms as a means to decide which of their possible actions they will apply in a given situation. This works as follows:

  * Events such as denunciation, paying extortion, shopping and so on trigger messages to  agents in the neighbourhood. If an event is related to more than one norm, several messages are broadcast by the agent which triggered the event. Each of these messages contains a reference to a norm (usually the norm or norms which is or are followed or violated by the action). A recipient of such a message updates those of its memory entries which refer to the specified norm according to whether the action is performed by itself or by another agent and whether the message contains a punishment or a sanction. This is implemented in a series of `update-` procedures (the `update-` procedures combine the invocation and the updates).

  * When an agent has to choose between different action options (including the option of doing nothing) it calculates a probability (`calculate-propensity-from` for actions controlled by only one norm, and `propensity-to` for actions controlled by two conflicting norms) for each of the action options which in turn depends on a rationally calculated "individual drive" (implemented in the procedure `calculate-my-individual-drive-to` with respect to the action named as the procedure's argument) and a "normative drive" which is calculated from the salience of the norm or norms involved in the action option. The salience of the norm, in turn, is calculated according to a complicated formula (implemented in the procedure `calculate-my-normative-drive-to`) which combines the memory of 
    * cases when this agent abided by the respective norm or violated it,

    * cases when this agent observed norm compliances and violations in its neighbourhood,

    * cases when this agent received punishments or sanctions and

    * cases when this agent heard about, applied or personally received invocations of the respective norm.

  * When an action is related to more than one norm (as is the case with events when pizzo is paid --- as this violates the `DO-NOT-PAY-EXTORTION` norm and at the same time complies with the `PAY-EXTORTION-AS-EVERYBODY-DOES` norm, the decision considers only the one with the higher salience.

**Shops** serve for providing the population with goods and services of any type. To keep things simple, these goods and services are not detailed. Shops receive payment from their customers and bear the fixed and variable costs of their business by paying into a funds which is evenly distributed to the population which is considered to provide the shops with the necessary supply (both in goods and sevrices) --- to keep things simple here, too, the households of the population receive an equal share of the overall period income of the shops, as if all of them served as suppliers and workers for the shops equally. 

Shops are often approached by criminals for "pizzo" which they can refuse at the risk of being severely punished. They can avoid this with a certain propensity to call the police (`denunciation-propensity`), denouncing the extorters and having them prosecuted. When a shop decides to denounce an extorter it joins an "addio-pizzo" movement and makes this fact known to everybody (and to the modeller by changing its colour from blue to red). When a shop decides not to denounce and the extorter (only if it is listed in the criminal records) is observed by the police, the victim collaborates as a witness (not as a denouncer), the extorter is prosecuted and the victim is punished for not not denouncing (it receives both a norm violation and a punishment message with respect to the `DENOUNCE-EXTORTION` norm).

In case shops are approached by more than one extorter at the same time --- this happens mainly in the initial phase and represents what might have happened when mafia-like organisations first came into being --- the shops decide whom to pay to, and the successful extorter will then protect the shop against the rivalling extorters. When due to extortion and punishment the asset of a shop falls below zero, it is closed and does not participate in the trading process until it is compensated from a funds filled by the confiscated wealth of the extorters.

In the norm version, shops know about three norms, `DENOUNCE-EXTORTION`,  `DO-NOT-PAY-EXTORTION` and `PAY-EXTORTION-AS-EVERYBODY-DOES`.

**Consumers** choose a shop for purchasing their goods. They have a certain propensity `addio-pizzo-threshold`  to choose shops belonging to the "addio-pizzo" movement. If their current shop is closed, they choose another, preferably belonging to the "addio-pizzo" movement and preferably having only a small number of customers (the reason for this is two-fold: they want to avoid crowded shops, and shops with only few customers should get a chance to prosper).

In the norm version, consumers know about two norms, `DO-NOT-SHOP-AT-EXTORTION-PAYER` and `DENOUNCE-EXTORTION`  (but these are not yet completely implemented, perhaps as it is difficult for consumers to observe an extortion which they could denounce).

**Extorters** start their career as individual criminals and approach the nearest reachable shop, asking for a "pizzo" which is a certain proportion (either `extortion-level-LOW` or `extortion-level-HIGH` depending on the type the extorter belongs to) of its revenue per period. When the shop refuses and the police fails to successfully prosecute the extorter, the latter punishes the shop, taking away a certain proportion  of all its assets (either `punishment-severity-LOW` or `punishment-severity-HIGH`, again depending on the type the extorter belongs to). It is understood that all assets of a shop are easily convertible into money, there are no physical assets which could be destroyed. Punishment becomes public, even when the victim does not officially denounce the extorter, the name of the extorter is added to the criminal records, and this extorter is now under observation. 

If the police hinders the extorter from punishing, the extorter is kept in investigation custody such that it cannot act any longer during the current period. If it is convicted it is brought to jail for a certain number of periods, and all its assets are confiscated and transferred into a funds from which in turn punished shops can be compensated (following a first come--first served principle). If several extorters approach the same shop at the same time, one of them is selected by the shop to protect the shop against rivalling extorters, and the latter subordinate to the former, forming a family and eventually a hierarchy, for instance in case the successful extorter is already subordinate to someone else; if any rivalling extorters already belong to families, the family hierarchy is not changed.

In the norm version, extorters know about two norms, `DO-NOT-BETRAY-COLLEAGUES` and `ABJURE-CRIME` (but these are not yet implemented).

At the end of each period extorters embedded in a family structure pay a tribute of `solidarity * wealth` to their respective leaders, and these leaders in turn distribute equal shares of their `wealth * solidarity` to their followers.

Extorters can collaborate with the police (become "pentiti") with a certain probability (`ruefulness`) in the phase when they are in investigation custody. This propensity is currently exogenous, but in a future version it will be controlled by the two norms `DO-NOT-BETRAY-COLLEAGUES` and `ABJURE-CRIME` mentioned above. If they decide to behave this way they become inactive forever and denounce their neighbours in the network whose names are then added to the criminal records. Pentiti are removed from the family tree and do no longer participate in the redistribution of wealth within their former family.

**Police** try to prosecute a denounced extorter and are successful  with a certain probability (`my-prosecution-propensity`) which in the norm version depends on their earlier experience. Moreover they keep criminal records for all extorter agents which ever were denounced in the past. If such an extorter which has a criminal record comes into the range of vision of police, it is also prosecuted. Arrested extorters cannot continue their activities during the current tick (they are in investigative custody).

In the norm version they know about two norms, `ANXIETY-IS-JUSTIFIED` and `TRY-HARD-TO-IMPRISON` (but these are not yet, or eventually poorly, implemented).

Beside the police which try to arrest extorters found by denunciation or observation there is also a court which can condemn an extorter found guilty. In this case they spend a longer time in jail (but this is not yet, or eventually poorly, implemented: extorters only stay in investigation custody until the end of the period and are never convicted --- it will be empirically interesting to find out under which conditions courts convict extorters and which norms they follow).

## HOW TO USE IT

Set the `initial-...` sliders before pressing `setup`. This determines the numbers of the different breeds in the world. There is currently no guarantee that arbitrary combinations of the `initial-...` sliders yield reasonable results. The same applies to the sliders which determine wealth and income.

Press `setup` to populate the world with all these agents. As usual, `go` will run the simulation continuously, while `go once` will run one tick.

The `constant-random-seed?` switch allows to run the model with the same random seed for different parameter combinations. If it is set OFF, every run starts with a new random seed.

If the `debug?` choser is on, output will be written to the file logfile.txt. Each new run is preceded with the date and time of the start of the run unless the file is deleted. NOT TO BE USED in the applet version!

The red and blue extortion links can be switched off with the `show-extortion-links?` switch.

The two groups of plots show what their headlines suggest. The block in the upper right corner contains histograms of norm saliences and of action propensities, the block in the lower right corder contains numbers of shops and extorters for different categories and amounts of wealth these possess.The percentages of different extortion outcomes is also plotted as an average of the past 10 cycles. The last of these moving averages can also be output in the behaviour space version such that it can be analysed as 

If the `batch-version?` choser is on and the `norm-version?` slider is off, the sliders for `extortion-level-...`, `punishment-severity-...`, `prosecution-propensity`, `denunciation-propensity` and `addio-pizzo-threshold` have no effect. Instead random values are assigned to these variables. This choser should only be set on in the BehaviorSpace mode.

If the `norm-version?` switch is off, the model behaves more or less exactly like the former version http://ccl.northwestern.edu/netlogo/models/community/ARDERS.

If both `batch-version?`and `norm-version?`switches are on, multiple runs with the same combination of all relevant paremeters can be executed. In a future version, there will also be a random setting for the parameters which are relevant for the norm version.

For the norm version the sliders `addio-pizzo-threshold` and `denunciation-propensity` do not take any effect as these two propensities are calculated endogenously and separately for each shop and consumer, respectively. The same applies to the `prosecution-propensity` slider, as the propensity of a police officer to prosecute also depends on the individual drive and the normative drive calculated from the salience of the two respective norms. 

The calculation consists of two steps: the individual drive of shops to denounce and/or to pay is determined by the risk of being extorted compared to the benefit of being protected by the successful extorter. The latter is currently and exogenous variable (`benefit-for-victims`).  The individual drive of other kinds of agents is still a constant set to zero. The normative drive depends on former experience with an agent's own actions and on observations made of normative behaviour of other agents' in the neighbourhood (see http://www.gloders.eu/images/Deliverables/GLODERS_D3-1.pdf, pp. 33-39).

For the norm version the following sliders control global variables:

* `LOCAL` determines the distance within which events can be observed
* `NDW` is the weight of the normative drive for calculating the decision probability, the sum of the two weights for individual drive and normative drive is 1.0
* `DISCOUNT` determines the weight of older memory contents (whenever a new event arrives, the number of all previous events is multiplied by `DISCOUNT` before 1 is added for the current event; thus with `DISCOUNT = 1.0` all events have the same weight inependent of their age.
* The standard initialisation of the memory of all agents with 0 could be unrealistic as it does not take account of the fact that any snapshot of the real world would start with real actors whose memory is not empty but filled with remembered compliances and violations of norms and past punishments and sanctions. This is why the slider `BACKGROUND` offers the possibility to initialise the agents according either to the standard (empty memories: `BACKGROUND = 0`) or to a "civic" scheme which is intolerant to extortion rackets (`0 < BACKGROUND < 100`) or to a "traditional" scheme which is tolerant to extortion rackets (`-100 < BACKGROUND < 0`), where the absolute amount of `BACKGROUND` denotes how intensive the "civic" or "traditional" scheme is.

A CSV file can be written (except in the batch version) in which every extortion case is documented much like in the Palermo database (but still with less information). As this would not work for applets, the respective code is a comment (search for "file" and remove the semicolons to make the code active).

## THINGS TO NOTICE

Target enterprises have an initial wealth uniformly distributed between the numbers on the respective min and max sliders, the income of a shop depends on the number of customers currently choosing it.

Extorters have two different extortion levels and two different severity levels (as in Nardin et al.) and a consumption per period which is currently fixed for all extorters at the same level. The difference between extortion and punishment severity levels can, of course, be suppressed by setting the sliders to the same value.

Extortion is a proportion (`extortion-level`) of the income per period, punishment for not paying is a proportion (`punishment-severity`) of the total wealth of the target.  

Often the local hierarchies agglomerate to one unique hierarchy.

The model keeps an extortion database of all attempted or successful extortion cases with information on whether the extorters were denounced, observed, prosecuted or condemned. (Not for the batch version, and in this version the respective code must be made active by removing the semicolons in all respective lines.)

The model calculates the main parameters of the norm salience distributions (mean and standard deviation).

## THINGS TO DISCUSS

The formula for calculating salience could be simplified. As weighting coefficients are multiples of 0.33 one could replace them with the respective multiples of 1.0 and change the `numerator` and the `denominator` accordingly. The formula is claimed in Deliverable 3.1 to have been extracted from Cialdini, R. B., Kallgren, C. A., Reno, R. R. (1990). A focus theory of normative conduct: A theoretical refinement and reevaluation of the role of norms in human behavior. Advances in Experimental Social Psychology. 24: 201–234. But it seems that only the terms used in this formula were extracted from this source (which does not say anything about the weights).

"DO-NOT-PAY-EXTORTION" and "PAY-EXTORTION-AS-EVERYBODY-DOES" are not just the two sides of a coin but two norms which are in conflict. As the effects of these norms exclude each other (extortion is either paid or not paid) it is necessary to discuss how the probability of paying is calculated. The simple version would be to assume that every violation of one of the two morms is a compliance with the other. But then sanctions and punishments of the two norms cannot be separated. Burning down the shop is certainly a punishment for a violation of the "PAY-EXTORTION-AS-EVERYBODY-DOES" norm, but what is it in terms of the "DO-NOT-PAY-EXTORTION" norm?

This model introduces norms relevant for the police and the extorter agents which have never been discussed among the GLODERS teams. Obviously, their behaviour, too, will be controlled by norms in the real world, and hence the model should include norms for these agent types, too. Without having implemented anything reasonable about them, the model contains two norms for each of them (see above). 

Not all norm invocations have been implemented yet, perhaps some norm-related messages have been forgotten. They will be inserted in future versions.

## THINGS TO TRY

The model can be used to find out which of the input parameters guiding the behaviour of the various kinds of agents have the greatest impact on the various output parameters (see Troitzsch 2014). It goes without saying that the model, although inspired by results of empirical research into individual behaviour done within the GLODERS project, has not yet been validated with respect to its output variables, thus it cannot be used to guide policy making, but it gives hints at which empirical macro variables to analyse.
The output generated by the model in a CSV file can be used to perform similar analyses as those made with the empirical data in the siciliy and Calabria database (629 cases of extortion which became known to the police and the courts, see the papers cited below).

## EXTENDING THE MODEL

The model could be extended by endowing the agents with even more learning capabilities. Particularly extorters could then optimise their behaviour as a reaction on punishment and sanctions. And certainly the relations between the public and the shops could be modelled in more detail, e.g. by having individual consumers work for one shop and purchase different kinds of goods from several different shops.

## NETLOGO FEATURES

Nothing special. The code uses recursive functions to determine to which family an extorter belongs and to write up the hierarchy in the output window.

## RELATED MODELS

There are three mafia models in the community (http://ccl.northwestern.edu/netlogo/models/community/Siste%20Mafia33,%20edited%202, http://ccl.northwestern.edu/netlogo/models/community/The%20Mafia%20Model%20-%20Interaction%20between%20police,%20mafia%20and%20storewoners and http://ccl.northwestern.edu/netlogo/models/community/When%20Mafias%20and%20States%20Cohabitate) which I have not consulted so far. 
## CREDITS AND REFERENCES

The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007--2013) under grant agreement no. 315874 ([Global dynamics of extortion racket systems, GLODERS](http://www.gloders.eu)). These results reflect only the author’s views, and the European Union is not liable for any use that may be made of the information contained therein. The author thanks his colleagues in this and earlier projects for fruitful discussions over many years.

The model owes a lot to the Nardin et al. discussion paper and to the discussions within the GLODERS project. The GLODERS project will use this model as a proof of concept and a quick and dirty prototype of the final GLODERS simulator.


## HOW TO CITE

The model and some of its first results are documented in

http://www.gloders.eu/images/Deliverables/GLODERS_D2-3.pdf

Klaus G. Troitzsch (2015) Extortion Racket Systems as Targets for Agent-Based Simulation Models. Comparing Competing Simulation Models and Emprical Data. Submitted to Advances in
Complex Systems

## COPYRIGHT NOTICE

Written by Klaus G. Troitzsch 2013-2015. The model may be used and extended if the source is quoted and a note is sent to kgt@uni-koblenz.de
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    </enumeratedValueSet>
  </experiment>
  <experiment name="norm batch 2" repetitions="1000" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <metric>denunciation-propensity</metric>
    <metric>prosecution-propensity</metric>
    <metric>addio-pizzo-threshold</metric>
    <metric>background</metric>
    <metric>LOCAL</metric>
    <metric>DISCOUNT</metric>
    <metric>NDW</metric>
    <metric>ruefulness</metric>
    <metric>benefit-for-victims</metric>
    <metric>conviction-probability</metric>
    <metric>extortion-level-low</metric>
    <metric>punishment-severity-low</metric>
    <metric>mean-shop-wealth-addio-pizzo</metric>
    <metric>mean-shop-wealth-non-addio-pizzo</metric>
    <metric>n-families</metric>
    <metric>n-shops-non-addio-pizzo</metric>
    <metric>n-shops-addio-pizzo</metric>
    <metric>n-shops-still-paying</metric>
    <metric>addio-pizzo-shopping-percentage</metric>
    <metric>percentage-of-undetected-cases</metric>
    <metric>percentage-of-unreported-cases</metric>
    <metric>percentage-of-completed-extortions</metric>
    <metric>percentage-of-cases-with-arrest</metric>
    <metric>percentage-of-cases-with-punishment</metric>
    <metric>percentage-of-critical-consumers</metric>
    <metric>ticks</metric>
    <metric>all-means</metric>
    <metric>all-sds</metric>
    <metric>"##"</metric>
    <enumeratedValueSet variable="batch-version?">
      <value value="true"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="norm-version?">
      <value value="true"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="norm batch 3" repetitions="1000" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <metric>denunciation-propensity</metric>
    <metric>prosecution-propensity</metric>
    <metric>addio-pizzo-threshold</metric>
    <metric>background</metric>
    <metric>LOCAL</metric>
    <metric>DISCOUNT</metric>
    <metric>NDW</metric>
    <metric>ruefulness</metric>
    <metric>benefit-for-victims</metric>
    <metric>conviction-probability</metric>
    <metric>extortion-level-low</metric>
    <metric>punishment-severity-low</metric>
    <metric>mean-shop-wealth-addio-pizzo</metric>
    <metric>mean-shop-wealth-non-addio-pizzo</metric>
    <metric>n-families</metric>
    <metric>n-shops-non-addio-pizzo</metric>
    <metric>n-shops-addio-pizzo</metric>
    <metric>n-shops-still-paying</metric>
    <metric>addio-pizzo-shopping-percentage</metric>
    <metric>percentage-of-undetected-cases</metric>
    <metric>percentage-of-unreported-cases</metric>
    <metric>percentage-of-completed-extortions</metric>
    <metric>percentage-of-cases-with-arrest</metric>
    <metric>percentage-of-cases-with-punishment</metric>
    <metric>percentage-of-critical-consumers</metric>
    <metric>ticks</metric>
    <metric>all-means</metric>
    <metric>all-sds</metric>
    <metric>"##"</metric>
    <enumeratedValueSet variable="batch-version?">
      <value value="true"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="norm-version?">
      <value value="true"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="non norm batch 3" repetitions="1000" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <metric>denunciation-propensity</metric>
    <metric>prosecution-propensity</metric>
    <metric>addio-pizzo-threshold</metric>
    <metric>background</metric>
    <metric>LOCAL</metric>
    <metric>DISCOUNT</metric>
    <metric>NDW</metric>
    <metric>ruefulness</metric>
    <metric>benefit-for-victims</metric>
    <metric>conviction-probability</metric>
    <metric>extortion-level-low</metric>
    <metric>punishment-severity-low</metric>
    <metric>mean-shop-wealth-addio-pizzo</metric>
    <metric>mean-shop-wealth-non-addio-pizzo</metric>
    <metric>n-families</metric>
    <metric>n-shops-non-addio-pizzo</metric>
    <metric>n-shops-addio-pizzo</metric>
    <metric>n-shops-still-paying</metric>
    <metric>addio-pizzo-shopping-percentage</metric>
    <metric>percentage-of-undetected-cases</metric>
    <metric>percentage-of-unreported-cases</metric>
    <metric>percentage-of-completed-extortions</metric>
    <metric>percentage-of-cases-with-arrest</metric>
    <metric>percentage-of-cases-with-punishment</metric>
    <metric>percentage-of-critical-consumers</metric>
    <metric>ticks</metric>
    <metric>all-means</metric>
    <metric>all-sds</metric>
    <metric>"##"</metric>
    <enumeratedValueSet variable="batch-version?">
      <value value="true"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="norm-version?">
      <value value="false"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="norm batch 4" repetitions="1000" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <metric>denunciation-propensity</metric>
    <metric>prosecution-propensity</metric>
    <metric>addio-pizzo-threshold</metric>
    <metric>background</metric>
    <metric>LOCAL</metric>
    <metric>DISCOUNT</metric>
    <metric>NDW</metric>
    <metric>ruefulness</metric>
    <metric>benefit-for-victims</metric>
    <metric>conviction-probability</metric>
    <metric>extortion-level-low</metric>
    <metric>punishment-severity-low</metric>
    <metric>mean-shop-wealth-addio-pizzo</metric>
    <metric>mean-shop-wealth-non-addio-pizzo</metric>
    <metric>n-families</metric>
    <metric>n-shops-non-addio-pizzo</metric>
    <metric>n-shops-addio-pizzo</metric>
    <metric>n-shops-still-paying</metric>
    <metric>addio-pizzo-shopping-percentage</metric>
    <metric>percentage-of-undetected-cases</metric>
    <metric>percentage-of-unreported-cases</metric>
    <metric>percentage-of-completed-extortions</metric>
    <metric>percentage-of-cases-with-arrest</metric>
    <metric>percentage-of-cases-with-punishment</metric>
    <metric>percentage-of-critical-consumers</metric>
    <metric>ticks</metric>
    <metric>all-means</metric>
    <metric>all-sds</metric>
    <metric>"##"</metric>
    <enumeratedValueSet variable="batch-version?">
      <value value="true"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="norm-version?">
      <value value="true"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="non norm batch 4" repetitions="1000" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <metric>denunciation-propensity</metric>
    <metric>prosecution-propensity</metric>
    <metric>addio-pizzo-threshold</metric>
    <metric>background</metric>
    <metric>LOCAL</metric>
    <metric>DISCOUNT</metric>
    <metric>NDW</metric>
    <metric>ruefulness</metric>
    <metric>benefit-for-victims</metric>
    <metric>conviction-probability</metric>
    <metric>extortion-level-low</metric>
    <metric>punishment-severity-low</metric>
    <metric>mean-shop-wealth-addio-pizzo</metric>
    <metric>mean-shop-wealth-non-addio-pizzo</metric>
    <metric>n-families</metric>
    <metric>n-shops-non-addio-pizzo</metric>
    <metric>n-shops-addio-pizzo</metric>
    <metric>n-shops-still-paying</metric>
    <metric>addio-pizzo-shopping-percentage</metric>
    <metric>percentage-of-undetected-cases</metric>
    <metric>percentage-of-unreported-cases</metric>
    <metric>percentage-of-completed-extortions</metric>
    <metric>percentage-of-cases-with-arrest</metric>
    <metric>percentage-of-cases-with-punishment</metric>
    <metric>percentage-of-critical-consumers</metric>
    <metric>ticks</metric>
    <metric>all-means</metric>
    <metric>all-sds</metric>
    <metric>"##"</metric>
    <enumeratedValueSet variable="batch-version?">
      <value value="true"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="norm-version?">
      <value value="false"/>
    </enumeratedValueSet>
  </experiment>
</experiments>
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