scarcity_v2.nlogo

extensions [table csv]

patches-own [resources]
turtles-own [


  labour age utility predationRes predationGoods protection production dict stratsum transfer technology experience resources-agent wealth goods calendar attackz risk-taking strategy-list strategy-utility-dict strategy-counter-dict strategy-success-dict current-strategy-success max-age]

globals [alpha beta lambda csv-list condition first-resource-shock first-resource-shock-end second-resource-shock second-resource-shock-end third-resource-shock third-resource-shock-end]


to setup

  clear-all

  ;random-seed 5

  ;resize-world 0 environment-size 0 environment-size

  ;; The below are factors used for the production equation
  set alpha random-normal 0.03 0.005
  set beta random-normal 0.03 0.005
  set lambda random-normal 0.03 0.005

  ;; The below are times when the resource shocks are inflicted on the environment, and when they end

  ;let t random-normal 2500 500
  set first-resource-shock 2500
  ;was round random-normal 2500 500
  set first-resource-shock-end first-resource-shock + 1000
  ; was first-resource-shock + round random-normal resource-shock-duration 100

  ;let j random-normal 5000 500
  set second-resource-shock 5000
  set second-resource-shock-end second-resource-shock + 1000

  ;let r random-normal 7500 500
  set third-resource-shock 7500
  set third-resource-shock-end third-resource-shock + 1000


  set csv-list []

  ifelse model-version = "scarcity" [set condition "scarcity"][set condition "control"]

  ;; create agends based on a slider (slider allows you to pick how many agents)
  ;crt num-agents [
  ;setxy random-xcor random-ycor

  ;set color white
  ;set shape "person"

  ;]

  ask patches [
    sprout 1 ]


  ask turtles [
    create-links-with turtles-on neighbors4
  ]
  ;    if any? other turtles in-radius num-connections [
  ;      repeat num-connections [ create-link-with one-of other turtles in-radius connections-radius ]]

  ask turtles [


    ;; Turtles owning stuff
    set age 0
    ;; set risk-tolerance
    set utility 0
    set labour effort-per-tick
    set predationRes 0
    set predationGoods 0
    set production 0
    set risk-taking random-normal 12 3
    set protection 0
    set max-age random-normal 2500 500
    ;; This has to be changed according to risk sensing or whatever
    set transfer 0
    set technology 1
    set experience 0
    set goods 0
    set attackz 0
    set resources-agent 0
    ; Attackz is a variable used to measure how many times the
    ; turtles have been attacked recently.
    set wealth 1
    ;; Yeah so I dunno abt wealth - they don;t really specify it in the paper.
    ;; So I'll just leave it at 1 I guess?


    ; Everything strategy

    set current-strategy-success 0

    ;; First we make a list with 3 bits, where each bit either activates or doesnt active
    ;; A particular gene - predation of goods, predation of resources or production

    set strategy-list (list random 2 random 2 random 2)

    ;; Then we make a strategy-utility-dictionary
    ;; This thing allows us to record how much utility an agent has produced with his current
    ;; strategy, giving us the possibility to see what is the best strategy so far for the agent
    set strategy-utility-dict table:make
    table:put strategy-utility-dict strategy-list 0


    ; Then we make a strategy-counter
    ; This will allow us to calculate the best strategy - as it will be calculated via
    ; Best strategy = total utility generated / how many ticks the strategy has been in use

    set strategy-counter-dict table:make
    table:put strategy-counter-dict strategy-list 0


    ; And then we combine the two above to calculate the current success of the strategy
    ; In a new dictionary

    set strategy-success-dict table:make
    table:put strategy-success-dict strategy-list 0

    set calendar table:make
    table:put calendar age 0
  ]



  ;; Let's give patches resources.
  ask patches [
    set resources resources-per-patch
    set pcolor green
    ;;Uniform accross all patches - that's how they do it in the paper right?
  ]

  reset-ticks

end


to go

  ;; So, as per paper, they first check their age and if they're too old they
  ;; die.
  ask turtles [
    reset-stats
    ;death
    ;; Turned off for now.
    set protection calculate-protection
    ;; First, the agent calculates how much effort or labour to allocate towards protection.
    set labour labour - protection
    ;; Then that amount is substracted from the total labour amount of the agent

    let effort-allocations effort-allocation ;; QUESTION HERE - HOW TO REFACTOR THIS FUNCTION. Like this, it's also a reporter now :)

    set predationRes item 0 effort-allocations
    set predationGoods item 1 effort-allocations
    set production item 2 effort-allocations

    set goods calculate-production
    ;; Now, if the agent has a production gene active, he produces a certain number of goods
    set experience experience + production / 10000
    ;; After he produces goods, his experience increases by the number of goods he has produced, scaled down.
    ;; How much experience?


    ;;AH: when you change the code to fix ordering, move this up to before turtle variables are reset each round. And then reset it
    set resources-agent 0
    ;; Now that the agent has produced goods from resources (which he acquired during the last round), we reset his resources to 0.

    set resources-agent gather-resources
    ;; Agent collects resources from the patch he is standing on.


  ]
  ask turtles [
    interact-with-neighbor ;; QUESTION HERE - NEEDS REFACTORING?

    ;set experience experience + 0.001
    set age age + 1
    ;; The agent ages by one tick, we register that here.

    table:put calendar age 0
    ;; This table acts as a calendar for the agent to keep track when he was attacked - so that he can allocate his efforts towards protection accordingly
    set utility utility + goods
    ;; Utility is a measure of how many goods the agent has produced in total up to this tick

    increment-utility
    ; This function helps track how much utility has the current strategy generated throughout the agents lifespan
    increment-counter
    ; This function helps track how many ticks the current strategy has been used
    calculate-strategy-success
    ; And this function calculates how succesful the current strategy is - by dividing total utility generated using the strategy by number of ticks it has been utilized.
    strategy-change
    ; Every round, the agent has a 0.4% chance of "mutating" a new random strategy.
    best-strategy-adaptation
    ; Similarly, every round, the agent has a 0.4% chance of switching to his most succesful strategy.
  ]
  tick
  resource-shock
  ; Enable below functions to produce CSV files for different simulation runs.
  ;prep-csv
  ;write-csv
end

to interact-with-neighbor
  ; Select a random neighbour and interact with it
  let neighbor one-of link-neighbors
  if neighbor != nobody [

    ; First checks if the predation of resources "gene" is active
    ; If so - proceeds to predates resources
    if predationRes != 0 [
      ; Below is the conflict function from the paper (Eq. 3)
      let transferino (predationRes / (predationRes + ([protection] of neighbor + predationRes))) ;  AH: bug here, I think the below is what they do

      set transfer transferino
      ; The outcome of the conflict is added to the resources
      set resources-agent resources-agent + transfer
      ask neighbor [
        ; The outcome of the conflict is substracted from neighbours resources
        set resources-agent resources-agent - transfer
        ; Make a note in his calendar that he was attacked
        table:put calendar age 1

      ]
    ]

    ; The below is the same but for Goods instead of Resources.
    if predationGoods != 0 [
      let transferino (predationGoods / (predationGoods + ([protection] of neighbor + predationGoods)))
      set transfer transferino
      set goods goods + transfer
      ask neighbor [
        set goods goods - transfer
        table:put calendar age 1
      ]
    ]

    ;; Lastly we give an opportunity to change the strategy list according to neighbors current strategy success.
    if current-strategy-success > [current-strategy-success] of neighbor [
      let i random 100
      let j strategy-list
      if i < 0.4 [
        ask neighbor [
          set strategy-list j
          if table:has-key? strategy-utility-dict strategy-list = FALSE [table:put strategy-utility-dict strategy-list 0]
          if table:has-key? strategy-counter-dict strategy-list = FALSE [table:put strategy-counter-dict strategy-list 0]
          if table:has-key? strategy-success-dict strategy-list = FALSE [table:put strategy-success-dict strategy-list 0]]
      ]
    ]
  ]
end

; This numbers of this needs to be checked. Like whether the resulting numbers are too low
; Or too high.
to-report calculate-production
  ; Checks if production "gene" is active"
  ; Below is Cobb-Douglas production function from the paper (Eq. 2)

    report production ^ alpha * (technology * (1 + experience) * sqrt wealth) ^ beta * ((1 + resources-agent) ^ lambda)

end




; Every tick, the agents gather resources of the patch they are standing on
to-report gather-resources
  if resources > 0 [
    report resources
  ]
end



to death
  if age = max-age [

    let i strategy-list

    hatch number-of-offspring [

      if any? other turtles in-radius 10 [
        repeat 10 [ create-link-with one-of other turtles in-radius 10 ]

        set age 0
        set utility 0
        set labour 100
        set predationRes 0
        set predationGoods 0
        set production 0
        set risk-taking random-normal 12 3
        set protection 0
        set max-age random-normal 2500 500
        set transfer 0
        set technology 1
        set experience 0
        set goods 0
        set attackz 0
        set wealth 1

        set strategy-list i

        set current-strategy-success 0

        set strategy-utility-dict table:make
        table:put strategy-utility-dict strategy-list 0

        set strategy-counter-dict table:make
        table:put strategy-counter-dict strategy-list 0

        set strategy-success-dict table:make
        table:put strategy-success-dict strategy-list 0


        set calendar table:make
        table:put calendar age 0


      ]
    ]

    die ]
end

; A function that allocates labour (which is can be thought of as 8 hours per day, here - 100 units)
; Labour is distributed equally to genes that are active - predation of resouces, goods or production
; Before this distribution, part of labour is firstly allocated to protection (see above)
to-report effort-allocation
  ;code here

  let predR labour / sum strategy-list * item 0 strategy-list
  let predG labour / sum strategy-list * item 1 strategy-list
  let prod labour / sum strategy-list * item 2 strategy-list

  report (list predR predG prod)

  ;
  ;
  ;
  ;  ]
  ;  if sum strategy-list = 0 [
  ;    if item 0 strategy-list = 1 [set predationRes labour / 1]
  ;    if item 1 strategy-list = 1 [set predationGoods labour / 1]
  ;    if item 2 strategy-list = 1 [set production labour / 1]
  ;  ]
  ;
  ;  if sum strategy-list = 1 [
  ;    if item 0 strategy-list = 1 [set predationRes labour / 1]
  ;    if item 1 strategy-list = 1 [set predationGoods labour / 1]
  ;    if item 2 strategy-list = 1 [set production labour / 1]
  ;  ]
  ;
  ;  if sum strategy-list = 2 [
  ;    if item 0 strategy-list = 1 [set predationRes labour / 2]
  ;    if item 1 strategy-list = 1 [set predationGoods labour / 2]
  ;    if item 2 strategy-list = 1 [set production labour / 2]
  ;  ]
  ;
  ;  if sum strategy-list = 3 [
  ;    if item 0 strategy-list = 1 [set predationRes labour / 3]
  ;    if item 1 strategy-list = 1 [set predationGoods labour / 3]
  ;    if item 2 strategy-list = 1 [set production labour / 3]
  ;  ]

end

; At the end of each tick, some turtle parameters are reset.
to reset-stats
  set goods 0
  set predationRes 0
  set predationGoods 0
  set production 0
  set protection 0
  set labour effort-per-tick
  set transfer 0
  set attackz 0
end

; Function for protection allocation based on danger (as measured by
; how many times the turtle has been attacked in the last 10 iterations)
; and risk-taking level which is assigned at birth (mean 12 + sd 3).

to protection-allocation2


end


to-report calculate-protection

  ;; The reason we brach based on ticks is that turtles should not learn from the first 10 ticks because otherwise we get too
  ;; strong learning effects from just one or a few experiences.

  ifelse ticks <= 10 [
    report risk-taking
  ]
  [
    let agez age
    repeat 10 [
      set agez agez - 1
      set attackz attackz + table:get calendar agez
    ]
    if attackz != 0 [
      report risk-taking * sqrt attackz
    ]
    if attackz = 0 [
      report risk-taking * 1
    ]
  ]

end

to best-strategy-adaptation

  let j random 100

  if j <= 4 [

    let i max table:values strategy-success-dict

    foreach (table:keys strategy-success-dict) [ x -> if table:get strategy-success-dict x = i [ set strategy-list x ]
    ]
  ]

end

to strategy-change

  let j random 100

  if j <= 4 [

    set strategy-list (list random 2 random 2 random 2)
    if table:has-key? strategy-utility-dict strategy-list = FALSE [table:put strategy-utility-dict strategy-list 0]
    if table:has-key? strategy-counter-dict strategy-list = FALSE [table:put strategy-counter-dict strategy-list 0]
    if table:has-key? strategy-success-dict strategy-list = FALSE [table:put strategy-success-dict strategy-list 0]

  ]

end

to increment-utility

  let i table:get strategy-utility-dict strategy-list
  table:put strategy-utility-dict strategy-list i + goods

end

to increment-counter
  let i table:get strategy-counter-dict strategy-list
  table:put strategy-counter-dict strategy-list i + 1

end

to calculate-strategy-success

  let i table:get strategy-utility-dict strategy-list
  let j table:get strategy-counter-dict strategy-list
  table:put strategy-success-dict strategy-list i / j
  set current-strategy-success table:get strategy-success-dict strategy-list


end

; procedure to write some turtle properties to a file
;to write-turtles-to-csv
; we use the `of` primitive to make a list of lists and then
; use the csv extension to write that list of lists to a file.
;csv:to-file "turtles.csv" [ (list xcor ycor size color heading) ] of turtles
;end


; So we have a list of lists that we convert to a CSV file. I guess what we need is a list of lists?
; So I guess the list stack to make columns.
; Then I need a list of 1) number of ticks and 2) sum [protection] of turtles 3) sum

to prep-csv
  if ticks >= 1500 [
    let i (list ticks sum [protection] of turtles sum [predationRes] of turtles sum [predationGoods] of turtles sum [production] of turtles condition)
    set csv-list lput i csv-list
  ]
end

to resource-shock

  if model-version = "scarcity" [

    if ticks = first-resource-shock [

      if shock-type = "line" [

        ask patches with [ pycor < min-pycor + shock-row-number ] [
          set resources resource-shock-intensity
          set pcolor brown ]

        if shock-type = "random" [

          ask n-of resource-shock-area patches [
            set resources resource-shock-intensity
            set pcolor brown
          ]

    ]]]

    if ticks = first-resource-shock-end [

      ask patches [
        set resources 100
        set pcolor green
      ]

    ]

    if ticks = second-resource-shock [

      if shock-type = "line" [

        ask patches with [ pycor < min-pycor + shock-row-number ] [
          set resources resource-shock-intensity
          set pcolor brown ]]

      if shock-type = "random" [

        ask n-of resource-shock-area patches [
          set resources resource-shock-intensity
          set pcolor brown
      ]]


    ]

    if ticks = second-resource-shock-end [

      ask patches [
        set resources 100
        set pcolor green
      ]

    ]

    if ticks = third-resource-shock [

      if shock-type = "line" [

        ask patches with [ pycor < min-pycor + shock-row-number ] [
          set resources resource-shock-intensity
          set pcolor brown ]
      ]

      if shock-type = "random" [

        ask n-of resource-shock-area patches [
          set resources resource-shock-intensity
          set pcolor brown
        ]
      ]
    ]

    if ticks = third-resource-shock-end [
      ask patches [
        set resources 100
        set pcolor green
      ]
    ]
  ]

end

to write-csv

  if ticks = 10000 [

    csv:to-file "export_control_test.csv" csv-list

  ]
end
@#$#@#$#@
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Effort allocation plot
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"" ""
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"predGoods" 1.0 0 -955883 true "" "plot sum [predationGoods] of turtles"
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@#$#@#$#@
## WHAT IS IT?

(a general understanding of what the model is trying to show or explain)

## HOW IT WORKS

(what rules the agents use to create the overall behavior of the model)

## HOW TO USE IT

(how to use the model, including a description of each of the items in the Interface tab)

## THINGS TO NOTICE

(suggested things for the user to notice while running the model)

## THINGS TO TRY

(suggested things for the user to try to do (move sliders, switches, etc.) with the model)

## EXTENDING THE MODEL

(suggested things to add or change in the Code tab to make the model more complicated, detailed, accurate, etc.)

## NETLOGO FEATURES

(interesting or unusual features of NetLogo that the model uses, particularly in the Code tab; or where workarounds were needed for missing features)

## RELATED MODELS

(models in the NetLogo Models Library and elsewhere which are of related interest)

## CREDITS AND REFERENCES

(a reference to the model's URL on the web if it has one, as well as any other necessary credits, citations, and links)
@#$#@#$#@
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Rectangle -7500403 true true 127 79 172 94
Polygon -7500403 true true 195 90 240 150 225 180 165 105
Polygon -7500403 true true 105 90 60 150 75 180 135 105

plant
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0
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Polygon -7500403 true true 135 255 90 210 45 195 75 255 135 285
Polygon -7500403 true true 165 255 210 210 255 195 225 255 165 285
Polygon -7500403 true true 135 180 90 135 45 120 75 180 135 210
Polygon -7500403 true true 165 180 165 210 225 180 255 120 210 135
Polygon -7500403 true true 135 105 90 60 45 45 75 105 135 135
Polygon -7500403 true true 165 105 165 135 225 105 255 45 210 60
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sheep
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Circle -1 true true 70 65 162
Circle -1 true true 150 105 120
Polygon -7500403 true false 218 120 240 165 255 165 278 120
Circle -7500403 true false 214 72 67
Rectangle -1 true true 164 223 179 298
Polygon -1 true true 45 285 30 285 30 240 15 195 45 210
Circle -1 true true 3 83 150
Rectangle -1 true true 65 221 80 296
Polygon -1 true true 195 285 210 285 210 240 240 210 195 210
Polygon -7500403 true false 276 85 285 105 302 99 294 83
Polygon -7500403 true false 219 85 210 105 193 99 201 83

square
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square 2
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Rectangle -16777216 true false 60 60 240 240

star
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Polygon -7500403 true true 151 1 185 108 298 108 207 175 242 282 151 216 59 282 94 175 3 108 116 108

target
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Circle -7500403 true true 0 0 300
Circle -16777216 true false 30 30 240
Circle -7500403 true true 60 60 180
Circle -16777216 true false 90 90 120
Circle -7500403 true true 120 120 60

tree
false
0
Circle -7500403 true true 118 3 94
Rectangle -6459832 true false 120 195 180 300
Circle -7500403 true true 65 21 108
Circle -7500403 true true 116 41 127
Circle -7500403 true true 45 90 120
Circle -7500403 true true 104 74 152

triangle
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0
Polygon -7500403 true true 150 30 15 255 285 255

triangle 2
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0
Polygon -7500403 true true 150 30 15 255 285 255
Polygon -16777216 true false 151 99 225 223 75 224

truck
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0
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Polygon -7500403 true true 296 193 296 150 259 134 244 104 208 104 207 194
Rectangle -1 true false 195 60 195 105
Polygon -16777216 true false 238 112 252 141 219 141 218 112
Circle -16777216 true false 234 174 42
Rectangle -7500403 true true 181 185 214 194
Circle -16777216 true false 144 174 42
Circle -16777216 true false 24 174 42
Circle -7500403 false true 24 174 42
Circle -7500403 false true 144 174 42
Circle -7500403 false true 234 174 42

turtle
true
0
Polygon -10899396 true false 215 204 240 233 246 254 228 266 215 252 193 210
Polygon -10899396 true false 195 90 225 75 245 75 260 89 269 108 261 124 240 105 225 105 210 105
Polygon -10899396 true false 105 90 75 75 55 75 40 89 31 108 39 124 60 105 75 105 90 105
Polygon -10899396 true false 132 85 134 64 107 51 108 17 150 2 192 18 192 52 169 65 172 87
Polygon -10899396 true false 85 204 60 233 54 254 72 266 85 252 107 210
Polygon -7500403 true true 119 75 179 75 209 101 224 135 220 225 175 261 128 261 81 224 74 135 88 99

wheel
false
0
Circle -7500403 true true 3 3 294
Circle -16777216 true false 30 30 240
Line -7500403 true 150 285 150 15
Line -7500403 true 15 150 285 150
Circle -7500403 true true 120 120 60
Line -7500403 true 216 40 79 269
Line -7500403 true 40 84 269 221
Line -7500403 true 40 216 269 79
Line -7500403 true 84 40 221 269

wolf
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0
Polygon -16777216 true false 253 133 245 131 245 133
Polygon -7500403 true true 2 194 13 197 30 191 38 193 38 205 20 226 20 257 27 265 38 266 40 260 31 253 31 230 60 206 68 198 75 209 66 228 65 243 82 261 84 268 100 267 103 261 77 239 79 231 100 207 98 196 119 201 143 202 160 195 166 210 172 213 173 238 167 251 160 248 154 265 169 264 178 247 186 240 198 260 200 271 217 271 219 262 207 258 195 230 192 198 210 184 227 164 242 144 259 145 284 151 277 141 293 140 299 134 297 127 273 119 270 105
Polygon -7500403 true true -1 195 14 180 36 166 40 153 53 140 82 131 134 133 159 126 188 115 227 108 236 102 238 98 268 86 269 92 281 87 269 103 269 113

x
false
0
Polygon -7500403 true true 270 75 225 30 30 225 75 270
Polygon -7500403 true true 30 75 75 30 270 225 225 270
@#$#@#$#@
NetLogo 6.2.0
@#$#@#$#@
@#$#@#$#@
@#$#@#$#@
<experiments>
  <experiment name="base-1" repetitions="4" sequentialRunOrder="false" runMetricsEveryStep="true">
    <setup>setup</setup>
    <go>go</go>
    <timeLimit steps="10000"/>
    <metric>mean [protection] of turtles</metric>
    <metric>mean [predationRes] of turtles</metric>
    <metric>mean [predationGoods] of turtles</metric>
    <metric>mean [production] of turtles</metric>
    <metric>standard-deviation [protection] of turtles</metric>
    <metric>standard-deviation [predationRes] of turtles</metric>
    <metric>standard-deviation [predationGoods] of turtles</metric>
    <metric>standard-deviation [production] of turtles</metric>
    <enumeratedValueSet variable="model-version">
      <value value="&quot;scarcity&quot;"/>
      <value value="&quot;normal&quot;"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="base-2-random-patch" repetitions="10" sequentialRunOrder="false" runMetricsEveryStep="true">
    <setup>setup</setup>
    <go>go</go>
    <timeLimit steps="7000"/>
    <metric>mean [protection] of turtles</metric>
    <metric>mean [predationRes] of turtles</metric>
    <metric>mean [predationGoods] of turtles</metric>
    <metric>mean [production] of turtles</metric>
    <metric>standard-deviation [protection] of turtles</metric>
    <metric>standard-deviation [predationRes] of turtles</metric>
    <metric>standard-deviation [predationGoods] of turtles</metric>
    <metric>standard-deviation [production] of turtles</metric>
    <enumeratedValueSet variable="resource-shock-area">
      <value value="15"/>
      <value value="30"/>
      <value value="45"/>
      <value value="60"/>
      <value value="75"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="model-version">
      <value value="&quot;scarcity&quot;"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="shock-type">
      <value value="&quot;random&quot;"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="base-2-line-patch" repetitions="10" sequentialRunOrder="false" runMetricsEveryStep="true">
    <setup>setup</setup>
    <go>go</go>
    <timeLimit steps="7000"/>
    <metric>mean [protection] of turtles</metric>
    <metric>mean [predationRes] of turtles</metric>
    <metric>mean [predationGoods] of turtles</metric>
    <metric>mean [production] of turtles</metric>
    <metric>standard-deviation [protection] of turtles</metric>
    <metric>standard-deviation [predationRes] of turtles</metric>
    <metric>standard-deviation [predationGoods] of turtles</metric>
    <metric>standard-deviation [production] of turtles</metric>
    <enumeratedValueSet variable="shock-row-number">
      <value value="1"/>
      <value value="2"/>
      <value value="3"/>
      <value value="4"/>
      <value value="5"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="model-version">
      <value value="&quot;scarcity&quot;"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="shock-type">
      <value value="&quot;line&quot;"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="base-2-normal" repetitions="10" sequentialRunOrder="false" runMetricsEveryStep="true">
    <setup>setup</setup>
    <go>go</go>
    <timeLimit steps="7000"/>
    <metric>mean [protection] of turtles</metric>
    <metric>mean [predationRes] of turtles</metric>
    <metric>mean [predationGoods] of turtles</metric>
    <metric>mean [production] of turtles</metric>
    <metric>standard-deviation [protection] of turtles</metric>
    <metric>standard-deviation [predationRes] of turtles</metric>
    <metric>standard-deviation [predationGoods] of turtles</metric>
    <metric>standard-deviation [production] of turtles</metric>
    <enumeratedValueSet variable="model-version">
      <value value="&quot;normal&quot;"/>
    </enumeratedValueSet>
  </experiment>
</experiments>
@#$#@#$#@
@#$#@#$#@
default
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0.0 1 1.0 0.0
0.2 0 0.0 1.0
link direction
true
0
Line -7500403 true 150 150 90 180
Line -7500403 true 150 150 210 180
@#$#@#$#@
0
@#$#@#$#@