Andros-Spica_MusicalChairs/Musical Chairs REVISITED_v2.nlogo
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;;; GNU GENERAL PUBLIC LICENSE ;;;
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;;  The Musical Chairs model - A model of the interaction between farming and herding (REVISITED v2)
;;  Copyright (C) 2016 Andreas Angourakis (andros.spica@gmail.com)
;;
;;  This program is free software: you can redistribute it and/or modify
;;  it under the terms of the GNU General Public License as published by
;;  the Free Software Foundation, either version 3 of the License, or
;;  (at your option) any later version.
;;
;;  This program is distributed in the hope that it will be useful,
;;  but WITHOUT ANY WARRANTY; without even the implied warranty of
;;  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
;;  GNU General Public License for more details.
;;
;;  You should have received a copy of the GNU General Public License
;;  along with this program.  If not, see <http://www.gnu.org/licenses/>.

;;;;;;;;;;;;;;;;;
;;;;; BREEDS ;;;;
;;;;;;;;;;;;;;;;;

breed [ stakeholders stakeholder ]

;;;;;;;;;;;;;;;;;
;;; VARIABLES ;;;
;;;;;;;;;;;;;;;;;

globals
[
  totalPatches

  ;;; modified parameters
  initH initF
  intGrowthF intGrowthH maxExtGrowthF maxExtGrowthH
  hrmi herdingIntegration farmingIntegration

  ;;; counters and final measures
  countLandUseF countLandUseH
  competitions landUseChangeEvents
  farmingDemand farmingGrowth farmingDeterrence farmingBalance
  herdingDemand herdingGrowth herdingDeterrence herdingBalance
  meanFarmingIntensity meanHerdingIntensity
  meanFarmingIndependence meanHerdingIndependence
]

patches-own [ landUse myStakeholder contenders ]

stakeholders-own [ hasLand activity intensity independence ]

;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;;; SETUP ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
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to setup

  clear-all

  set totalPatches count patches

  ;;; setup parameters depending on the type of experiment
  if (typeOfExperiment = "random")
  [
    ; set random seed
    let aSeed new-seed
    random-seed aSeed
    set seed aSeed

    set intGrowthF 0.01 + random-float farming_intrinsic_growth_rate
    set maxExtGrowthF 0.001 + random-float max_farming_extrinsic_growth_rate
    set farmingIntegration random-float 1
    set intGrowthH 0.01 + random-float herding_intrinsic_growth_rate
    set maxExtGrowthH 0.001 + random-float max_herding_extrinsic_growth_rate
    set herdingIntegration random-float 1
    set initH random round ((init_herding / 100) * totalPatches)
    set initF random round ((init_farming / 100) * totalPatches)
    set hrmi ((1 + (random-float 10) ) / (1 + (random-float 10) )) ;; set a random value between 0.1 and 10 (around 1)
  ]
  if (typeOfExperiment = "defined by GUI")
  [
    ; set random seed
    random-seed seed

    set intGrowthF farming_intrinsic_growth_rate
    set maxExtGrowthF max_farming_extrinsic_growth_rate
    set farmingIntegration farming_integration
    set intGrowthH herding_intrinsic_growth_rate
    set maxExtGrowthH max_herding_extrinsic_growth_rate
    set herdingIntegration herding_integration
    set initH round ((init_herding / 100) * totalPatches)
    set initF round ((init_farming / 100) * totalPatches)
    set hrmi herding_relative_max_intensity
  ]
  if (typeOfExperiment = "defined by expNumber")
  [
    ; set random seed
    let aSeed new-seed
    random-seed aSeed
    set seed aSeed

    load-experiment
  ]

  ;;; set land use according to the parameter setting (position is arbitrary and has no consequence)
  ask patches [ set landUse "N" set myStakeholder nobody set contenders (turtle-set) ]
  ask n-of initF patches
  [
    set landUse "F"
    sprout-stakeholders 1
    [
      set hidden? true
      set hasLand true
      set activity "F"
      set intensity random-float 1
      set independence random-float 1
    ]
    set myStakeholder one-of stakeholders-here
  ]
  ask n-of initH patches with [landUse = "N"]
  [
    set landUse "H"
    sprout-stakeholders 1
    [
      set hidden? true
      set hasLand true
      set activity "H"
      set intensity random-float hrmi
      set independence random-float 1
    ]
    set myStakeholder one-of stakeholders-here
  ]

  ;;; initialize visualization
  update_visualization

  reset-ticks

end

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;;; CYCLE ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;

to go

  ;;; This procedure is the cycle of the model (what happens during one "tick").

  reset-counters

  growth

  landUse-expansion

  check_competitions

  update_visualization

  tick
  if ticks > endSimulation [stop]

end

to reset-counters

  ;;; This procedure reset all counters which are used either during the cycle or summarized at the "update-visualization" procedure.

  set farmingDemand 0
  set herdingDemand 0
  set farmingGrowth 0
  set farmingDeterrence 0
  set herdingGrowth 0
  set herdingDeterrence 0
  set competitions 0
  set landUseChangeEvents 0

end

to growth

  ;;; This procedure calculates the demand for each land use class, based on both the intrinsic and extrinsic growth rates of each of them.
  ;;; Note that growth rates are dependent on parameters, but also on the context, and may vary from one "tick" to another.

  ;;; FARMING
  ;;; Intrinsic Demand
  ask patches with [landUse = "F"]
  [
    if ( random-float 1 <= intGrowthF )
    [
      sprout-stakeholders 1
      [
        set hidden? true
        set hasLand false ;;; still landless
        set activity "F"
        set intensity [intensity] of myStakeholder
        set independence [independence] of myStakeholder
      ]
      set farmingDemand farmingDemand + 1
    ]
  ]
  ;;; Extrinsic Demand
  let extF (round (maxExtGrowthF * ( totalPatches - countLandUseF ) ) )
  repeat extF
  [
    ask patch 0 0
    [
      sprout-stakeholders 1
      [
        set hidden? true
        set hasLand false ;;; still landless
        set activity "F"
        set intensity random-float 1
        set independence random-float 1
      ]
    ]
    set farmingDemand farmingDemand + 1
  ]

  ;;; HERDING
  ;;; Intrinsic Growth
  ask patches with [landUse = "H"]
  [
    if ( random-float 1 <= intGrowthH )
    [
      sprout-stakeholders 1
      [
        set hidden? true
        set hasLand false ;;; still landless
        set activity "H"
        set intensity [intensity] of myStakeholder
        set independence [independence] of myStakeholder
      ]
      set herdingDemand herdingDemand + 1
    ]
  ]
  ;;; Extrinsic Demand
  let extH (round (maxExtGrowthH * ( totalPatches - countLandUseH ) ) )
  repeat extH
  [
    ask patch max-pxcor max-pycor
    [
      sprout-stakeholders 1
      [
        set hidden? true
        set hasLand false ;;; still landless
        set activity "H"
        set intensity random-float 1
        set independence random-float 1
      ]
    ]
    set herdingDemand herdingDemand + 1
  ]

end

to landUse-expansion

  ;;; This procedure calls for the expansion procedures of farming and herding, intentionally in this order.

  farming-expansion
  herding-expansion

end

to farming-expansion

  if (any? stakeholders with [ activity = "F" AND hasLand = false ])
  [
    ask stakeholders with [ activity = "F" AND hasLand = false ]
    [
      if (any? patches with [landUse != "F"]) ;;; Fit-to-maximum exclusion
      [
        let me self
        ask one-of patches
        [
          let aPatch self
          if (landUse != "F") ;;; Density-dependent exclusion
          [
            ifelse (landUse = "N")
            [
              ;;; the farming stakeholder will start using the unused land
              set landUse "F"
              set myStakeholder me
              ask me [ set hasLand true move-to aPatch ]

              set landUseChangeEvents landUseChangeEvents + 1
              set farmingGrowth farmingGrowth + 1
            ]
            [
              if ( [independence] of me > (count patches with [landUse = "H"] / totalPatches) ) ;;; Volition-opportunity exclusion
              [
                ;;; the farming stakeholder will start using the pastureland
                set landUse "F"
                ask myStakeholder [ set hasLand false ]
                set myStakeholder me
                ask me [ set hasLand true move-to aPatch ]

                set landUseChangeEvents landUseChangeEvents + 1
                set farmingGrowth farmingGrowth + 1
                set herdingDeterrence herdingDeterrence + 1
              ]
            ]
          ]
        ]
      ]
    ]
  ]
  ask stakeholders with [ activity = "F" AND hasLand = false ] [ die ]

end

to herding-expansion

  ;;; reset herding patches (herds go back not necessarily to the same patch), but keep track of the herding stakeholders that already used the territory
  let oldHerdingStakeholders [myStakeholder] of patches with [landUse = "H"]
  ask patches with [landUse = "H"]
  [
    ask myStakeholder [ set hasLand false ]
    set myStakeholder nobody
  ]

  if (any? stakeholders with [ activity = "H" AND hasLand = false ])
  [
    ask stakeholders with [ activity = "H" AND hasLand = false ]
    [
      if (any? patches with [myStakeholder = nobody]) ;;; Fit-to-maximum exclusion
      [
        let me self
        let aPatch one-of patches
        if (member? me oldHerdingStakeholders)
        [
          set aPatch one-of patches with [myStakeholder = nobody] ;;; herding stakeholders that already visited the territory do not suffer the Density-dependent exclusion
        ]
        ask aPatch
        [
          ask me [ move-to aPatch ]
          ifelse (myStakeholder = nobody) ;;; Density-dependent exclusion
          [
            ifelse (landUse = "N")
            [
              ;;; the herding stakeholder will start using the unused land
              set landUse "H"
              set myStakeholder me
              ask me [ set hasLand true ]

              set landUseChangeEvents landUseChangeEvents + 1
              set herdingGrowth herdingGrowth + 1
            ]
            [
              ;;; the herding stakeholder will start using the temporally unoccupied land
              set myStakeholder me
              ask me [ set hasLand true ]
            ]
          ]
          [
            if (landUse = "F")
            [
              ;;; the herding stakeholder will press to use a farming patch
              set contenders (turtle-set contenders me)
            ]
          ]
        ]
      ]
    ]
  ]

  ;;; rangelands not claimed will be considered free land (no land use)
  if (any? patches with [landUse = "H" and myStakeholder = nobody] ) [ ask patches with [landUse = "H" and myStakeholder = nobody] [ set landUse "N" ] ]

end

to check_competitions

  ask patches with [ landUse = "F" AND count contenders > 0 ]
  [
    repeat count contenders [ resolve_competition ]
  ]
  ask stakeholders with [ activity = "H" AND hasLand = false ] [ die ]

end

to resolve_competition

  ;;; set competition conditions
  let aPatch self
  ;;;;; select one farming stakeholder and its supporters, calculate the intensity of the farming land use involved in a land use unit
  let defender myStakeholder
  let farmingSupporters round (farmingIntegration * ((count stakeholders with [activity = "F"]) - 1))
  let farmingSupport 0
  if (farmingSupporters > 0) [ set farmingSupport sum [intensity] of n-of farmingSupporters stakeholders with [activity = "F" AND self != defender] ]
  let farmingIntensity ([intensity] of myStakeholder + farmingSupport )

  ;;;;; select one herding stakeholder and its supporters, calculate the intensity of the herding land use to be involved in the same land use unit
  ;;; get contender and exlude it from contenders
  let contender one-of contenders
  set contenders contenders with [self != contender]
  let herdingSupporters round (herdingIntegration * ((count stakeholders with [activity = "H"]) - 1))
  let herdingSupport 0
  if (herdingSupporters > 0) [ set herdingSupport sum [intensity] of n-of herdingSupporters stakeholders with [activity = "H" AND self != contender] ]
  let herdingIntensity ([intensity] of contender + herdingSupport )

  ;;;;; calculate the ratio of intensities, the index of opportunity and the incentives for relinquish, all taken from the perspective of herding land use
  let ratio_of_intensities  (herdingIntensity /(farmingIntensity + herdingIntensity))
  let index_of_opportunity ((count patches with [landUse = "F"]) / totalPatches)
  let incentives_to_relinquish (1 - (ratio_of_intensities * index_of_opportunity))

  ask contender
  [
    ;;; Does the herding stakeholder attempt to replace the farming stakeholder?
    ifelse ( independence < incentives_to_relinquish)

    ;;; No. The herding stakeholder is repressed.
    [ die ]

    ;;; Yes. A competitive situation is produced.
    [
      set competitions (competitions + 1)

      ;;; Does the competitive situation evolves into a land use change event?
      ifelse (random-float 1 < ratio_of_intensities)

      ;;; Yes. The farming stakeholder is repressed.
      [
        ask defender [ die ]
        set myStakeholder contender
        set hasLand true
        set landUse "H"
        set landUseChangeEvents landUseChangeEvents + 1
        set herdingGrowth herdingGrowth + 1
        set farmingDeterrence farmingDeterrence + 1
      ]

      ;;; No. The herding stakeholder is repressed.
      [ die ]
    ]
  ]

end

to update_visualization

  set farmingBalance (farmingGrowth - farmingDeterrence)
  set herdingBalance (herdingGrowth - herdingDeterrence)

  set countLandUseF count patches with [landUse = "F"]
  set countLandUseH count patches with [landUse = "H"]

  ifelse (countLandUseF > 0)
  [
    set meanFarmingIntensity (mean [intensity] of stakeholders with [activity = "F"])
    set meanFarmingIndependence (mean [independence] of stakeholders with [activity = "F"])
  ]
  [
    set meanFarmingIntensity ""
    set meanFarmingIndependence ""
  ]

  ifelse (countLandUseH > 0)
  [
    set meanHerdingIntensity (mean [intensity] of stakeholders with [activity = "H"]) / hrmi
    set meanHerdingIndependence (mean [independence] of stakeholders with [activity = "H"])
  ]
  [
    set meanHerdingIntensity ""
    set meanHerdingIndependence ""
  ]

  update-patches

end

to update-patches

  ask patches
  [
    set pcolor brown
    if (landUse = "F")
    [ set pcolor green ]
    if (landUse = "H")
    [ set pcolor yellow ]
  ]

end

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;;;;;;;;;;;; Parametrization from file ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;

to load-experiment

let FilePath "SensAnalysis//exp//"
let filename (word FilePath "exp_" expNumber ".csv")
file-open filename
while [not file-at-end?]
[
  set intGrowthF file-read
  set maxExtGrowthF file-read
  set farmingIntegration file-read
  set intGrowthH file-read
  set maxExtGrowthH file-read
  set herdingIntegration file-read
  set initH file-read
  set initF file-read
  set hrmi file-read

  set endSimulation file-read ;- 1500 ;; use this to cut down the time of simulation (e.g. if the file reads 2000)
]
file-close

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

The Musical Chairs (MC) model intends to explore the conditions for the emergence and change of land use patterns in Central Asian oases and similar contexts. Land use pattern is conceptualized as the proportion between the area used for mobile livestock breeding (herding) and sedentary agriculture (farming), the main forms of livelihood from the Neolithic to the Industrial Revolution. We assume that these different forms of land use interact in recurrent competitive situations (presumably, but not necessarily, yearly-basis), given that the land useful for both activities is limited and there is a pressure to increase both classes of land use, due to demographic and/or economic growth. This is the first and most simple model of a series dedicated to this objective. See RELATED MODELS below.

## HOW IT WORKS

The MC model is a mechanism that assign stakeholders and their particular variant of land use (agents or "turtles") to the land use by them (patches). It represents a context where farming (sedentary land use) and herding (seasonal mobile) land use compete seasonally for a limited space. Although patches DO represent spatial units, spatial relationships (neighborhood, distance) are not relevant in this model.

The cycle begins with the calculation of the demand for land of both farming and herding (`growth` procedure). The demand may be generated by intrinsic (_density dependent_) or extrinsic (_density independent_) factors. Demand is here translated as the introduction of new stakeholders, which either inherit the traits of the "parent" stakeholder (if generated by intrinsic growth) or have random traits (if generated by extrinsic growth).

The satisfaction of all land use demand is done by the expansion of each land use class (`expansion` procedures). First, expansion is constrained by the density of the respective land use class. The more extended a land use class, the fewer opportunities to expand. Farming stakeholders attempting to settle over pastures can do it without causing a competitive situation (farming settling predates the return of herds). They will decide to settle by comparing their own dependence to herding stakeholders (trait `independence`) against the overall presence of herding in the territory, up to the moment. Moreover, herding stakeholders arrive in a random order and consider the access to pastureland to be open, which implies that older stakeholders have the additional risk of being put off by newer stakeholders. After the expansion procedure, some herding stakeholders may remain landless, some pressing against farming stakeholders (as `contenders`), others simply dispersing or exiting the territory.

The procedure `check-competitions` iterate over all patches resolving all competitions posed by the herding contenders. The `resolve-competition` procedure includes two steps: (1) the herding contender will be able to assess the probability of overcoming the influence of farming (`ratio_of_intensities`), the marginal value of the patch (`index_of_opportunity`), and compare them to its independence to farming; (2) if the contender insists producing a competitive situation, a stochastic test using the `ratio_of_intensities` will determine whether the contender occupies the patch or not.

## HOW TO USE IT

First, you should select the desired type of experiment (`typeOfExperiment`):

* "defined by GUI": all values introduced by the user in sliders, boxes, and choosers (except `expNumber`) will be applied.

* "random": randomly selects values for all the parameters (except `expNumber` and `endSimulation`).

* "defined by expNumber": the setup procedure will call for the `load-experiment` procedure, which set the parameters using the values of a "exp_<expNumber>.csv" file, if available. The seed for the random number generator is set randomly.

GUI elements:

* `endSimulation`: the number of cycles to simulate.

* `seed`: set the seed for the random number generator. The same integer number will always generate the same simulation, given the same parameter configuration.

* `init_farming`: the initial percentage of patches used for farming.

* `init_herding`: the initial percentage of patches used for herding.

* `farming_intrinsic_growth_rate`, `herding_intrinsic_growth_rate`: the intrinsic growth for farming/herding land use per patch (0.05 = 5%).

* `max_farming_extrinsic_growth_rate`, `max_herding_extrinsic_growth_rate`: the maximum value of the extrinsic growth for farming/herding land use (0.1 = 10%).

* `herding_relative_max_intensity`: the maximum intensity of herding stakeholders, relative to the maximum intensity of farming stakeholders, which always equals to __one__.

* `farming_integration`, `herding_integration`: the proportion of farming/herding stakeholders that will or can support their own land use class in a competitive situation.

## THINGS TO NOTICE

The MC model describes the implications of the alternation between a non-competitive period, where stakeholders and their activities grow their land use demand, and a competitive period, where both expanding forces press for their interests with asymmetric conditions (sedentary versus mobile activities). Simulations with balanced overall intensities (`herding_relative_max_intensity` around 1) and integration levels (`farming_integration` equal to `herding_integration`) show a clear trend favoring the expansion of farming.
The model demonstrates the role of competition in selecting for intensity and independence, but also how higher levels of integration smooth the selection for intensity.

## THINGS TO TRY

* Which parameters facilitate the formation of balanced land use patterns? Are these patterns stable?

## RELATED MODELS

TO DO

## CREDITS AND REFERENCES

Further information can be found in the ODD protocol and the following publication:

Angourakis et al. (2014) Land Use Patterns in Central Asia. Step 1: The Musical Chairs Model. Journal of Archaeological Method and Theory, Speacial Issue on Computer Simulation.
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    <metric>herdingDeterrence</metric>
    <metric>herdingBalance</metric>
    <metric>meanFarmingIntensity</metric>
    <metric>meanHerdingIntensity</metric>
    <metric>meanFarmingIndependence</metric>
    <metric>meanHerdingIndependence</metric>
    <enumeratedValueSet variable="herding_relative_max_intensity">
      <value value="0.1"/>
      <value value="0.2"/>
      <value value="0.5"/>
      <value value="1"/>
      <value value="2"/>
      <value value="5"/>
      <value value="10"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_farming_extrinsic_growth_rate">
      <value value="0"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_herding_extrinsic_growth_rate">
      <value value="0"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_integration">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_integration">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_herding">
      <value value="100"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_farming">
      <value value="100"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="ext0intg1_init100vs200" repetitions="10" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <timeLimit steps="600"/>
    <metric>totalPatches</metric>
    <metric>intGrowthF</metric>
    <metric>intGrowthH</metric>
    <metric>maxExtGrowthF</metric>
    <metric>maxExtGrowthH</metric>
    <metric>initH</metric>
    <metric>initF</metric>
    <metric>hrmi</metric>
    <metric>herdingIntegration</metric>
    <metric>farmingIntegration</metric>
    <metric>countLandUseF</metric>
    <metric>countLandUseH</metric>
    <metric>competitions</metric>
    <metric>landUseChangeEvents</metric>
    <metric>farmingDemand</metric>
    <metric>farmingGrowth</metric>
    <metric>farmingDeterrence</metric>
    <metric>farmingBalance</metric>
    <metric>herdingDemand</metric>
    <metric>herdingGrowth</metric>
    <metric>herdingDeterrence</metric>
    <metric>herdingBalance</metric>
    <metric>meanFarmingIntensity</metric>
    <metric>meanHerdingIntensity</metric>
    <metric>meanFarmingIndependence</metric>
    <metric>meanHerdingIndependence</metric>
    <enumeratedValueSet variable="herding_relative_max_intensity">
      <value value="0.1"/>
      <value value="0.2"/>
      <value value="0.5"/>
      <value value="1"/>
      <value value="2"/>
      <value value="5"/>
      <value value="10"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_farming_extrinsic_growth_rate">
      <value value="0"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_herding_extrinsic_growth_rate">
      <value value="0"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_integration">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_integration">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_herding">
      <value value="100"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_farming">
      <value value="200"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="ext0intg1_init200vs100" repetitions="10" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <timeLimit steps="600"/>
    <metric>totalPatches</metric>
    <metric>intGrowthF</metric>
    <metric>intGrowthH</metric>
    <metric>maxExtGrowthF</metric>
    <metric>maxExtGrowthH</metric>
    <metric>initH</metric>
    <metric>initF</metric>
    <metric>hrmi</metric>
    <metric>herdingIntegration</metric>
    <metric>farmingIntegration</metric>
    <metric>countLandUseF</metric>
    <metric>countLandUseH</metric>
    <metric>competitions</metric>
    <metric>landUseChangeEvents</metric>
    <metric>farmingDemand</metric>
    <metric>farmingGrowth</metric>
    <metric>farmingDeterrence</metric>
    <metric>farmingBalance</metric>
    <metric>herdingDemand</metric>
    <metric>herdingGrowth</metric>
    <metric>herdingDeterrence</metric>
    <metric>herdingBalance</metric>
    <metric>meanFarmingIntensity</metric>
    <metric>meanHerdingIntensity</metric>
    <metric>meanFarmingIndependence</metric>
    <metric>meanHerdingIndependence</metric>
    <enumeratedValueSet variable="herding_relative_max_intensity">
      <value value="0.1"/>
      <value value="0.2"/>
      <value value="0.5"/>
      <value value="1"/>
      <value value="2"/>
      <value value="5"/>
      <value value="10"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_farming_extrinsic_growth_rate">
      <value value="0"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_herding_extrinsic_growth_rate">
      <value value="0"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_integration">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_integration">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_herding">
      <value value="200"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_farming">
      <value value="100"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="ext0intg1_init200vs200" repetitions="10" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <timeLimit steps="600"/>
    <metric>totalPatches</metric>
    <metric>intGrowthF</metric>
    <metric>intGrowthH</metric>
    <metric>maxExtGrowthF</metric>
    <metric>maxExtGrowthH</metric>
    <metric>initH</metric>
    <metric>initF</metric>
    <metric>hrmi</metric>
    <metric>herdingIntegration</metric>
    <metric>farmingIntegration</metric>
    <metric>countLandUseF</metric>
    <metric>countLandUseH</metric>
    <metric>competitions</metric>
    <metric>landUseChangeEvents</metric>
    <metric>farmingDemand</metric>
    <metric>farmingGrowth</metric>
    <metric>farmingDeterrence</metric>
    <metric>farmingBalance</metric>
    <metric>herdingDemand</metric>
    <metric>herdingGrowth</metric>
    <metric>herdingDeterrence</metric>
    <metric>herdingBalance</metric>
    <metric>meanFarmingIntensity</metric>
    <metric>meanHerdingIntensity</metric>
    <metric>meanFarmingIndependence</metric>
    <metric>meanHerdingIndependence</metric>
    <enumeratedValueSet variable="herding_relative_max_intensity">
      <value value="0.1"/>
      <value value="0.2"/>
      <value value="0.5"/>
      <value value="1"/>
      <value value="2"/>
      <value value="5"/>
      <value value="10"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_farming_extrinsic_growth_rate">
      <value value="0"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_herding_extrinsic_growth_rate">
      <value value="0"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_integration">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_integration">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_herding">
      <value value="200"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_farming">
      <value value="200"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="ext25intg0_init100vs100" repetitions="10" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <timeLimit steps="600"/>
    <metric>totalPatches</metric>
    <metric>intGrowthF</metric>
    <metric>intGrowthH</metric>
    <metric>maxExtGrowthF</metric>
    <metric>maxExtGrowthH</metric>
    <metric>initH</metric>
    <metric>initF</metric>
    <metric>hrmi</metric>
    <metric>herdingIntegration</metric>
    <metric>farmingIntegration</metric>
    <metric>countLandUseF</metric>
    <metric>countLandUseH</metric>
    <metric>competitions</metric>
    <metric>landUseChangeEvents</metric>
    <metric>farmingDemand</metric>
    <metric>farmingGrowth</metric>
    <metric>farmingDeterrence</metric>
    <metric>farmingBalance</metric>
    <metric>herdingDemand</metric>
    <metric>herdingGrowth</metric>
    <metric>herdingDeterrence</metric>
    <metric>herdingBalance</metric>
    <metric>meanFarmingIntensity</metric>
    <metric>meanHerdingIntensity</metric>
    <metric>meanFarmingIndependence</metric>
    <metric>meanHerdingIndependence</metric>
    <enumeratedValueSet variable="herding_relative_max_intensity">
      <value value="0.1"/>
      <value value="0.2"/>
      <value value="0.5"/>
      <value value="1"/>
      <value value="2"/>
      <value value="5"/>
      <value value="10"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_farming_extrinsic_growth_rate">
      <value value="0.25"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_herding_extrinsic_growth_rate">
      <value value="0.25"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_integration">
      <value value="0"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_integration">
      <value value="0"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_herding">
      <value value="100"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_farming">
      <value value="100"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="ext25intg0_init100vs200" repetitions="10" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <timeLimit steps="600"/>
    <metric>totalPatches</metric>
    <metric>intGrowthF</metric>
    <metric>intGrowthH</metric>
    <metric>maxExtGrowthF</metric>
    <metric>maxExtGrowthH</metric>
    <metric>initH</metric>
    <metric>initF</metric>
    <metric>hrmi</metric>
    <metric>herdingIntegration</metric>
    <metric>farmingIntegration</metric>
    <metric>countLandUseF</metric>
    <metric>countLandUseH</metric>
    <metric>competitions</metric>
    <metric>landUseChangeEvents</metric>
    <metric>farmingDemand</metric>
    <metric>farmingGrowth</metric>
    <metric>farmingDeterrence</metric>
    <metric>farmingBalance</metric>
    <metric>herdingDemand</metric>
    <metric>herdingGrowth</metric>
    <metric>herdingDeterrence</metric>
    <metric>herdingBalance</metric>
    <metric>meanFarmingIntensity</metric>
    <metric>meanHerdingIntensity</metric>
    <metric>meanFarmingIndependence</metric>
    <metric>meanHerdingIndependence</metric>
    <enumeratedValueSet variable="farming_max_intensity">
      <value value="100"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_relative_max_intensity">
      <value value="0.1"/>
      <value value="0.2"/>
      <value value="0.5"/>
      <value value="1"/>
      <value value="2"/>
      <value value="5"/>
      <value value="10"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_farming_extrinsic_growth_rate">
      <value value="0.25"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_herding_extrinsic_growth_rate">
      <value value="0.25"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_integration">
      <value value="0"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_integration">
      <value value="0"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_herding">
      <value value="100"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_farming">
      <value value="200"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="ext25intg0_init200vs100" repetitions="10" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <timeLimit steps="600"/>
    <metric>totalPatches</metric>
    <metric>intGrowthF</metric>
    <metric>intGrowthH</metric>
    <metric>maxExtGrowthF</metric>
    <metric>maxExtGrowthH</metric>
    <metric>initH</metric>
    <metric>initF</metric>
    <metric>hrmi</metric>
    <metric>herdingIntegration</metric>
    <metric>farmingIntegration</metric>
    <metric>countLandUseF</metric>
    <metric>countLandUseH</metric>
    <metric>competitions</metric>
    <metric>landUseChangeEvents</metric>
    <metric>farmingDemand</metric>
    <metric>farmingGrowth</metric>
    <metric>farmingDeterrence</metric>
    <metric>farmingBalance</metric>
    <metric>herdingDemand</metric>
    <metric>herdingGrowth</metric>
    <metric>herdingDeterrence</metric>
    <metric>herdingBalance</metric>
    <metric>meanFarmingIntensity</metric>
    <metric>meanHerdingIntensity</metric>
    <metric>meanFarmingIndependence</metric>
    <metric>meanHerdingIndependence</metric>
    <enumeratedValueSet variable="herding_relative_max_intensity">
      <value value="0.1"/>
      <value value="0.2"/>
      <value value="0.5"/>
      <value value="1"/>
      <value value="2"/>
      <value value="5"/>
      <value value="10"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_farming_extrinsic_growth_rate">
      <value value="0.25"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_herding_extrinsic_growth_rate">
      <value value="0.25"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_integration">
      <value value="0"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_integration">
      <value value="0"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_herding">
      <value value="200"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_farming">
      <value value="100"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="ext25intg0_init200vs200" repetitions="10" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <timeLimit steps="600"/>
    <metric>totalPatches</metric>
    <metric>intGrowthF</metric>
    <metric>intGrowthH</metric>
    <metric>maxExtGrowthF</metric>
    <metric>maxExtGrowthH</metric>
    <metric>initH</metric>
    <metric>initF</metric>
    <metric>hrmi</metric>
    <metric>herdingIntegration</metric>
    <metric>farmingIntegration</metric>
    <metric>countLandUseF</metric>
    <metric>countLandUseH</metric>
    <metric>competitions</metric>
    <metric>landUseChangeEvents</metric>
    <metric>farmingDemand</metric>
    <metric>farmingGrowth</metric>
    <metric>farmingDeterrence</metric>
    <metric>farmingBalance</metric>
    <metric>herdingDemand</metric>
    <metric>herdingGrowth</metric>
    <metric>herdingDeterrence</metric>
    <metric>herdingBalance</metric>
    <metric>meanFarmingIntensity</metric>
    <metric>meanHerdingIntensity</metric>
    <metric>meanFarmingIndependence</metric>
    <metric>meanHerdingIndependence</metric>
    <enumeratedValueSet variable="herding_relative_max_intensity">
      <value value="0.1"/>
      <value value="0.2"/>
      <value value="0.5"/>
      <value value="1"/>
      <value value="2"/>
      <value value="5"/>
      <value value="10"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_farming_extrinsic_growth_rate">
      <value value="0.25"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_herding_extrinsic_growth_rate">
      <value value="0.25"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_integration">
      <value value="0"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_integration">
      <value value="0"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_herding">
      <value value="200"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_farming">
      <value value="200"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="ext25intg1_init100vs100" repetitions="10" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <timeLimit steps="600"/>
    <metric>totalPatches</metric>
    <metric>intGrowthF</metric>
    <metric>intGrowthH</metric>
    <metric>maxExtGrowthF</metric>
    <metric>maxExtGrowthH</metric>
    <metric>initH</metric>
    <metric>initF</metric>
    <metric>hrmi</metric>
    <metric>herdingIntegration</metric>
    <metric>farmingIntegration</metric>
    <metric>countLandUseF</metric>
    <metric>countLandUseH</metric>
    <metric>competitions</metric>
    <metric>landUseChangeEvents</metric>
    <metric>farmingDemand</metric>
    <metric>farmingGrowth</metric>
    <metric>farmingDeterrence</metric>
    <metric>farmingBalance</metric>
    <metric>herdingDemand</metric>
    <metric>herdingGrowth</metric>
    <metric>herdingDeterrence</metric>
    <metric>herdingBalance</metric>
    <metric>meanFarmingIntensity</metric>
    <metric>meanHerdingIntensity</metric>
    <metric>meanFarmingIndependence</metric>
    <metric>meanHerdingIndependence</metric>
    <enumeratedValueSet variable="herding_relative_max_intensity">
      <value value="0.1"/>
      <value value="0.2"/>
      <value value="0.5"/>
      <value value="1"/>
      <value value="2"/>
      <value value="5"/>
      <value value="10"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_farming_extrinsic_growth_rate">
      <value value="0.25"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_herding_extrinsic_growth_rate">
      <value value="0.25"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_integration">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_integration">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_herding">
      <value value="100"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_farming">
      <value value="100"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="ext25intg1_init100vs200" repetitions="10" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <timeLimit steps="600"/>
    <metric>totalPatches</metric>
    <metric>intGrowthF</metric>
    <metric>intGrowthH</metric>
    <metric>maxExtGrowthF</metric>
    <metric>maxExtGrowthH</metric>
    <metric>initH</metric>
    <metric>initF</metric>
    <metric>hrmi</metric>
    <metric>herdingIntegration</metric>
    <metric>farmingIntegration</metric>
    <metric>countLandUseF</metric>
    <metric>countLandUseH</metric>
    <metric>competitions</metric>
    <metric>landUseChangeEvents</metric>
    <metric>farmingDemand</metric>
    <metric>farmingGrowth</metric>
    <metric>farmingDeterrence</metric>
    <metric>farmingBalance</metric>
    <metric>herdingDemand</metric>
    <metric>herdingGrowth</metric>
    <metric>herdingDeterrence</metric>
    <metric>herdingBalance</metric>
    <metric>meanFarmingIntensity</metric>
    <metric>meanHerdingIntensity</metric>
    <metric>meanFarmingIndependence</metric>
    <metric>meanHerdingIndependence</metric>
    <enumeratedValueSet variable="herding_relative_max_intensity">
      <value value="0.1"/>
      <value value="0.2"/>
      <value value="0.5"/>
      <value value="1"/>
      <value value="2"/>
      <value value="5"/>
      <value value="10"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_farming_extrinsic_growth_rate">
      <value value="0.25"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_herding_extrinsic_growth_rate">
      <value value="0.25"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_integration">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_integration">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_herding">
      <value value="100"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_farming">
      <value value="200"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="ext25intg1_init200vs100" repetitions="10" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <timeLimit steps="600"/>
    <metric>totalPatches</metric>
    <metric>intGrowthF</metric>
    <metric>intGrowthH</metric>
    <metric>maxExtGrowthF</metric>
    <metric>maxExtGrowthH</metric>
    <metric>initH</metric>
    <metric>initF</metric>
    <metric>hrmi</metric>
    <metric>herdingIntegration</metric>
    <metric>farmingIntegration</metric>
    <metric>countLandUseF</metric>
    <metric>countLandUseH</metric>
    <metric>competitions</metric>
    <metric>landUseChangeEvents</metric>
    <metric>farmingDemand</metric>
    <metric>farmingGrowth</metric>
    <metric>farmingDeterrence</metric>
    <metric>farmingBalance</metric>
    <metric>herdingDemand</metric>
    <metric>herdingGrowth</metric>
    <metric>herdingDeterrence</metric>
    <metric>herdingBalance</metric>
    <metric>meanFarmingIntensity</metric>
    <metric>meanHerdingIntensity</metric>
    <metric>meanFarmingIndependence</metric>
    <metric>meanHerdingIndependence</metric>
    <enumeratedValueSet variable="herding_relative_max_intensity">
      <value value="0.1"/>
      <value value="0.2"/>
      <value value="0.5"/>
      <value value="1"/>
      <value value="2"/>
      <value value="5"/>
      <value value="10"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_farming_extrinsic_growth_rate">
      <value value="0.25"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_herding_extrinsic_growth_rate">
      <value value="0.25"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_integration">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_integration">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_herding">
      <value value="200"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_farming">
      <value value="100"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="ext25intg1_init200vs200" repetitions="10" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <timeLimit steps="600"/>
    <metric>totalPatches</metric>
    <metric>intGrowthF</metric>
    <metric>intGrowthH</metric>
    <metric>maxExtGrowthF</metric>
    <metric>maxExtGrowthH</metric>
    <metric>initH</metric>
    <metric>initF</metric>
    <metric>hrmi</metric>
    <metric>herdingIntegration</metric>
    <metric>farmingIntegration</metric>
    <metric>countLandUseF</metric>
    <metric>countLandUseH</metric>
    <metric>competitions</metric>
    <metric>landUseChangeEvents</metric>
    <metric>farmingDemand</metric>
    <metric>farmingGrowth</metric>
    <metric>farmingDeterrence</metric>
    <metric>farmingBalance</metric>
    <metric>herdingDemand</metric>
    <metric>herdingGrowth</metric>
    <metric>herdingDeterrence</metric>
    <metric>herdingBalance</metric>
    <metric>meanFarmingIntensity</metric>
    <metric>meanHerdingIntensity</metric>
    <metric>meanFarmingIndependence</metric>
    <metric>meanHerdingIndependence</metric>
    <enumeratedValueSet variable="herding_relative_max_intensity">
      <value value="0.1"/>
      <value value="0.2"/>
      <value value="0.5"/>
      <value value="1"/>
      <value value="2"/>
      <value value="5"/>
      <value value="10"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_farming_extrinsic_growth_rate">
      <value value="0.25"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_herding_extrinsic_growth_rate">
      <value value="0.25"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_integration">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_integration">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_herding">
      <value value="200"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_farming">
      <value value="200"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="randomized" repetitions="50" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <timeLimit steps="600"/>
    <metric>totalPatches</metric>
    <metric>intGrowthF</metric>
    <metric>intGrowthH</metric>
    <metric>maxExtGrowthF</metric>
    <metric>maxExtGrowthH</metric>
    <metric>initH</metric>
    <metric>initF</metric>
    <metric>hrmi</metric>
    <metric>herdingIntegration</metric>
    <metric>farmingIntegration</metric>
    <metric>countLandUseF</metric>
    <metric>countLandUseH</metric>
    <metric>competitions</metric>
    <metric>landUseChangeEvents</metric>
    <metric>farmingDemand</metric>
    <metric>farmingGrowth</metric>
    <metric>farmingDeterrence</metric>
    <metric>farmingBalance</metric>
    <metric>herdingDemand</metric>
    <metric>herdingGrowth</metric>
    <metric>herdingDeterrence</metric>
    <metric>herdingBalance</metric>
    <metric>meanFarmingIntensity</metric>
    <metric>meanHerdingIntensity</metric>
    <metric>meanFarmingIndependence</metric>
    <metric>meanHerdingIndependence</metric>
    <enumeratedValueSet variable="herding_relative_max_intensity">
      <value value="10"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_farming_extrinsic_growth_rate">
      <value value="0.25"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_intrinsic_growth_rate">
      <value value="0.04"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="max_herding_extrinsic_growth_rate">
      <value value="0.25"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="herding_integration">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="farming_integration">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_herding">
      <value value="100"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init_farming">
      <value value="100"/>
    </enumeratedValueSet>
  </experiment>
</experiments>
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