Genocide (Epstein Civil Unrest Model 2)

;; ===============================================================================
;; EPSTEIN'S CIVIL VIOLENCE MODEL II: ETHNIC CONFLICT AND GENOCIDE
;; ===============================================================================
;; This model simulates inter-group violence between two ethnic groups (blue and green)
;; with law enforcement attempting to maintain order. Based on Joshua Epstein's 
;; agent-based model of civil violence (2002).
;;
;; Key dynamics:
;; - Agents from different ethnic groups may engage in violence against each other
;; - Violence is driven by grievance (hardship + illegitimacy) vs. arrest risk
;; - Cops arrest violent agents, implementing bias through differential enforcement
;; - Population dynamics through agent reproduction (cloning)
;; ===============================================================================

;; ===============================================================================
;; DECLARATIONS
;; ===============================================================================

;; Two breeds: civilian agents (can be violent) and law enforcement (cops)
breed [ agents an-agent ]
breed [ cops cop ]

;; Global parameters used throughout the simulation
globals [
  k                   ; constant factor for arrest probability calculation
  cloning-probability ; per-turn probability of agent reproduction (0.05)
  imbalance-history
  sliding-window-size
  current-imbalance
  mean-imbalance
  imbalance-slope
  imbalance-metric
]

;; Agent and cop attributes
turtles-own [
  ethnic-group        ; 0 = blue group, 1 = green group (retained when converted to/from cop)
  risk-aversion       ; R, individual's risk tolerance (0-1), fixed for lifetime
  perceived-hardship  ; H, economic/social hardship level (0-1)
  recently-violent?   ; boolean: has this agent recently committed violence? (makes them arrestable)
  violence-timer      ; countdown: how many turns agent remains marked as violent
  jail-term           ; countdown: how many turns remain in jail (0 = not jailed)
  arrest-prob         ; calculated probability of arrest (used for bias implementation)
]

;; Patch-level caching for performance optimization
patches-own [
  neighborhood        ; cached agentset of patches within vision radius
]

;; ===============================================================================
;; INITIALIZATION PROCEDURES
;; ===============================================================================

to setup
  clear-all
  
  ;; Initialize global constants
  set k 2.3                   ; arrest probability scaling factor
  set cloning-probability 0.05 ; 5% chance of reproduction per turn per eligible agent
  set sliding-window-size 50
  set imbalance-history []
  set current-imbalance 0
  set mean-imbalance 0
  set imbalance-slope 0
  set imbalance-metric 0
  
  ;; Setup patches: color and cache neighborhoods
  ask patches [
    set pcolor gray - 1  ; slightly dark gray background
    set neighborhood patches in-radius vision  ; cache for performance
  ]
  
  ;; Validate density parameters
  if cop-density + initial-agent-density > 100 [
    user-message (word
      "The sum of cop-density and INITIAL-AGENT-DENSITY "
      "should not be greater than 100.")
    stop
  ]
  
  ;; Calculate total population
  let total-population round ((cop-density + initial-agent-density) * .01 * count patches)
  
  ;; STEP 1: Create all individuals as civilian agents first
  ;; Blue ethnic group
  create-agents round (total-population * blue-group-ratio / 100) [
    move-to one-of patches with [ not any? turtles-here ]
    set heading 0
    set ethnic-group 0           ; blue group identifier
    set risk-aversion random-float 1.0
    set perceived-hardship random-float 1.0
    set recently-violent? false  ; start peaceful
    set violence-timer 0
    set jail-term 0
    display-agent-2d
  ]
  
  ;; Green ethnic group
  create-agents round (total-population * (100 - blue-group-ratio) / 100) [
    move-to one-of patches with [ not any? turtles-here ]
    set heading 0
    set ethnic-group 1           ; green group identifier
    set risk-aversion random-float 1.0
    set perceived-hardship random-float 1.0
    set recently-violent? false  ; start peaceful
    set violence-timer 0
    set jail-term 0
    display-agent-2d
  ]
  
  ;; STEP 2: Convert designated proportion of agents to cops (peacekeepers)
  let target-cops round (cop-density * .01 * count patches)
  if target-cops > 0 [
    ask n-of (min list target-cops count agents) agents [
      set breed cops
      set recently-violent? false  ; cops never engage in ethnic violence
      display-cop
    ]
  ]
  
  ;; Initialize simulation clock
  reset-ticks
end 

;; ===============================================================================
;; MAIN SIMULATION LOOP
;; ===============================================================================

to go
  ;; Execute behavioral rules for all turtles
  ask turtles [
    ;; Rule M (Movement): Free agents and all cops move randomly within vision
    if (breed = agents and jail-term = 0) or breed = cops [ move ]
    
    ;; Rule V (Violence): Free, peaceful agents check for violence opportunities
    if breed = agents and jail-term = 0 and not recently-violent? 
      [ check-for-violence-opportunity ]
    
    ;; Rule C (Cops): Law enforcement arrests violent agents in their vicinity
    if breed = cops [ enforce ]
  ]
   
  ;; Population dynamics: agent reproduction (only non-jailed, non-violent agents)
  ask agents [
    if not recently-violent? and jail-term = 0 [
      if random-float 1 < cloning-probability [
        reproduce
      ]
    ]
  ]
  
  ;; Update timers: reduce jail sentences and violence visibility
  ask agents [ 
    if jail-term > 0 [ set jail-term jail-term - 1 ]
    if violence-timer > 0 [ 
      set violence-timer violence-timer - 1 
      if violence-timer = 0 [ set recently-violent? false ]  ; violence no longer visible
    ]
  ]
  
  ;; Dynamically adjust police force size based on slider
  adjust-cop-density
  
  ;; Update visual display
  ask agents [ display-agent-2d ]
  ask cops [ display-cop ]
  
  update-imbalance-metric
  
  ;; Advance simulation clock
  tick
end 

;; ===============================================================================
;; AGENT DECISION-MAKING: VIOLENCE
;; ===============================================================================

;; Agents evaluate whether to commit violence against other ethnic groups
;; Decision based on Epstein's grievance-risk model:
;; Violence occurs when: Grievance - (Risk-Aversion × Arrest-Probability) > Threshold

to check-for-violence-opportunity
  let current-neighborhood [neighborhood] of patch-here
  let my-ethnic-group ethnic-group
  let potential-targets agents-on current-neighborhood
  let targets turtle-set []
  
  ;; Identify potential victims: agents of different ethnicity who aren't jailed
  ask potential-targets [
    if ethnic-group != my-ethnic-group and jail-term = 0 [
      set targets (turtle-set targets self)
    ]
  ]
  
  ;; If potential targets exist, calculate decision to attack
  if any? targets [
    let grievance-level grievance
    let estimated-risk estimated-arrest-probability
    let net-risk risk-aversion * estimated-risk
    
    ;; Decision rule: attack if grievance exceeds risk by threshold
    if (grievance-level - net-risk > threshold) [
      ;; Commit act of violence: eliminate victim
      let victim one-of targets
      ask victim [ die ]
      ;; Become visible as violent (arrestable by cops)
      set recently-violent? true
      set violence-timer 3  ; remain visible/arrestable for 3 turns
    ]
  ]
end 

;; ===============================================================================
;; DYNAMIC POPULATION MANAGEMENT
;; ===============================================================================

;; Adjust cop density dynamically by converting between agents and cops
;; Allows real-time changes to policing levels via slider

to adjust-cop-density
  ;; Calculate target cop count based on current slider setting
  let target-cops round (cop-density * .01 * count patches)
  let current-cops count cops
  
  ;; Recruit more cops if needed (convert peaceful, free agents)
  if target-cops > current-cops [
    let cops-to-recruit (target-cops - current-cops)
    let available-agents agents with [ jail-term = 0 and not recently-violent? ]
    let can-recruit min list cops-to-recruit count available-agents
    
    if can-recruit > 0 [
      ask n-of can-recruit available-agents [
        convert-to-cop
      ]
    ]
  ]
  
  ;; Demobilize excess cops if needed (convert back to agents)
  if target-cops < current-cops [
    let cops-to-demobilize (current-cops - target-cops)
    ask n-of cops-to-demobilize cops [
      convert-to-agent
    ]
  ]
end 

;; Convert a civilian agent into a cop (recruitment/mobilization)

to convert-to-cop
  set breed cops
  set recently-violent? false  ; cops don't engage in ethnic violence
  set violence-timer 0
  set jail-term 0              ; clear any existing jail time
  display-cop
end 

;; Convert a cop back into a civilian agent (demobilization)

to convert-to-agent
  set breed agents
  ;; Retain civilian attributes: ethnic-group, hardship, risk-aversion
  set recently-violent? false  ; demobilized as peaceful citizen
  set violence-timer 0
  set jail-term 0              ; not jailed upon demobilization
  display-agent-2d
end 

;; ===============================================================================
;; MOVEMENT PROCEDURES
;; ===============================================================================

;; Agents and cops move to random empty patches within their vision
;; Empty = no other cops, only jailed agents allowed

to move  ; turtle procedure
  if movement? or breed = cops [
    let current-neighborhood [neighborhood] of patch-here
    ;; Find candidate patches: no cops, only jailed agents if any
    let targets current-neighborhood with [
      not any? cops-here and all? agents-here [ jail-term > 0 ]
    ]
    if any? targets [ move-to one-of targets ]
  ]
end 

;; ===============================================================================
;; AGENT ATTRIBUTES: GRIEVANCE AND RISK ASSESSMENT
;; ===============================================================================

;; Calculate agent's grievance level toward the other ethnic group
;; Based on Epstein's formula: G = H(1 - L)
;; Where H = hardship, L = inter-group legitimacy

to-report grievance
  ;; Legitimacy represents acceptance of other group's right to exist
  let legitimacy-value max list 0 min list 1 inter-group-legitimacy
  
  ;; Incarceration increases hardship perception
  let effective-hardship perceived-hardship
  if jail-term > 0 [ set effective-hardship effective-hardship + random-float 0.1 ]
  
  ;; Grievance increases with hardship and decreases with legitimacy
  report max list 0 min list 1 effective-hardship * (1 - legitimacy-value)
end 

;; Estimate probability of arrest based on local cop/violent-agent ratio
;; Epstein's formula: P = 1 - exp(-k × floor(C/A))
;; Where C = cops in vision, A = active (violent) agents in vision

to-report estimated-arrest-probability
  let current-neighborhood [neighborhood] of patch-here
  let c count cops-on current-neighborhood
  let v 1 + count (agents-on current-neighborhood) with [ recently-violent? ]
  ;; floor(C/V) creates threshold effect: if V > C, probability ≈ 0
  report 1 - exp (- k * floor (c / v))
end 

;; ===============================================================================
;; POPULATION DYNAMICS: REPRODUCTION
;; ===============================================================================

;; Agent reproduction through cloning with variation
;; Offspring inherit ethnic group and traits with small mutations

to reproduce
  ;; Find empty neighboring patch for offspring
  let empty-neighbors neighbors with [ not any? turtles-here ]
  if any? empty-neighbors [
    let target one-of empty-neighbors
    hatch 1 [
      move-to target
      ;; Inheritance: ethnic group from parent
      set ethnic-group [ethnic-group] of myself
      ;; Trait variation: hardship with small random change
      set perceived-hardship max list 0 min list 1 
        ([perceived-hardship] of myself + random-normal 0 0.1)
      ;; New random risk-aversion
      set risk-aversion random-float 1.0
      ;; Born peaceful and free
      set recently-violent? false
      set violence-timer 0
      set jail-term 0
      display-agent-2d
    ]
  ]
end 

;; ===============================================================================
;; LAW ENFORCEMENT: COP BEHAVIOR
;; ===============================================================================

;; Cops arrest violent agents within their vision
;; Implements police bias through differential arrest probabilities

to enforce
  let current-neighborhood [neighborhood] of patch-here
  ;; Check for any violent agents in vicinity
  if any? (agents-on current-neighborhood) with [ recently-violent? ] [
    let violent-agents1 (agents-on current-neighborhood) with [ recently-violent? ]
    
    ;; Calculate arrest probability for each violent agent (implements bias)
    ask violent-agents1 [
      let ethnicity ethnic-group
      
      ;; Base arrest probability is 100%
      set arrest-prob 1
      ;; Apply bias: reduce arrest probability for favored group
      ;; Negative bias favors blue (group 0), positive bias favors green (group 1)
      if (police-bias < 0 and ethnicity = 0) or (police-bias > 0 and ethnicity = 1) [
        set arrest-prob 1 - (abs(police-bias) * 0.5)  ; up to 50% reduction
      ]
    ]
    
    ;; Target agent with highest arrest probability (biased selection)
    let suspect max-one-of violent-agents1 [arrest-prob]
    move-to suspect
    ;; Attempt arrest based on calculated probability
    if random-float 1 < [arrest-prob] of suspect [
      ask suspect [
        set recently-violent? false  ; no longer visible as violent
        set violence-timer 0
        set jail-term random max-jail-term  ; random sentence length
      ]
    ]
  ]
end 

;; ===============================================================================
;; VISUALIZATION PROCEDURES
;; ===============================================================================

;; Display civilian agents with color coding:
;; RED = recently violent (arrestable)
;; DARK GRAY = jailed
;; BLUE/GREEN = peaceful, showing ethnic group

to display-agent-2d  ; agent procedure
  set shape "circle"
  
  ifelse recently-violent?
    [ set color red ]  ; violent agents visible to cops
    [ ifelse jail-term > 0
        [ set color black + 3 ]  ; jailed agents (dark gray)
        [ ;; Peaceful agents show ethnic identity
          ifelse ethnic-group = 0
            [ set color blue ]   ; blue ethnic group
            [ set color green ]  ; green ethnic group
        ]
    ]
end 

;; Display cops as cyan triangles

to display-cop
  set color cyan
  set shape "triangle"
end 

;; ===============================================================================
;; MONITORING REPORTERS
;; ===============================================================================
;; These reporters provide data for plots and monitors

;; Count free blue group agents (not jailed)

to-report blue-agents
  report count agents with [ ethnic-group = 0 and jail-term = 0 ]
end 

;; Count free green group agents (not jailed)

to-report green-agents
  report count agents with [ ethnic-group = 1 and jail-term = 0 ]
end 

;; Count currently violent agents (all ethnicities)

to-report violent-agents
  report count agents with [ recently-violent? ]
end 

;; Count all jailed agents

to-report jailed-agents
  report count agents with [ jail-term > 0 ]
end 

;; Count violent blue group agents

to-report blue-violent
  report count agents with [ ethnic-group = 0 and recently-violent? ]
end 

;; Count violent green group agents

to-report green-violent
  report count agents with [ ethnic-group = 1 and recently-violent? ]
end 

;; Count cops from blue ethnic group

to-report blue-cops
  report count cops with [ ethnic-group = 0 ]
end 

;; Count cops from green ethnic group

to-report green-cops
  report count cops with [ ethnic-group = 1 ]
end 

to update-imbalance-metric
  ; Count current populations (non-jailed agents)
  let blue-count count agents with [ethnic-group = 0 and jail-term = 0]
  let green-count count agents with [ethnic-group = 1 and jail-term = 0]
  
  ; Calculate imbalance: 0 = balanced, 1 = extinction
  ifelse blue-count > 0 and green-count > 0 [
    let min-pop min (list blue-count green-count)
    let max-pop max (list blue-count green-count)
    set current-imbalance 1 - (min-pop / max-pop)
  ][
    ; One group extinct
    set current-imbalance 1.0
  ]
  
  ; Add to history
  set imbalance-history lput current-imbalance imbalance-history
  
  ; Keep only last N values (sliding window)
  if length imbalance-history > sliding-window-size [
    set imbalance-history but-first imbalance-history
  ]
  
  ; Calculate metrics (only when we have enough data)
  if length imbalance-history >= sliding-window-size [
    calculate-imbalance-metrics
  ]
end 

to calculate-imbalance-metrics
  ; Calculate mean imbalance over window
  set mean-imbalance mean imbalance-history
  
  ; Calculate slope (trend): compare first half vs second half
  let half-window floor (sliding-window-size / 2)
  let first-half sublist imbalance-history 0 half-window
  let second-half sublist imbalance-history half-window sliding-window-size
  
  let first-mean mean first-half
  let second-mean mean second-half
  set imbalance-slope second-mean - first-mean
  
  ; Composite metric: mean × (1 + |slope|)
  ; Lower = better (more stable)
  set imbalance-metric mean-imbalance * (1 + abs imbalance-slope)
end 

to-report get-imbalance-metric
  ; This is your PRIMARY metric to MINIMIZE
  ; Combines average imbalance and trend
  report imbalance-metric
end 

to-report get-current-imbalance
  ; For monitoring: current tick's imbalance (0-1)
  report current-imbalance
end 

to-report get-mean-imbalance
  ; For monitoring: average imbalance over window
  report mean-imbalance
end 

to-report get-imbalance-slope
  ; For monitoring: trend (positive = worsening)
  report imbalance-slope
end