model.nlogo

globals [
  customer_patches
  feature_patches
  total_market_feature_set_ids
  has_gone_to_market?
  last_backlog_story
  max_initial_feature_set
]

breed [ customers customer ]
breed [ features feature ]
breed [ stories story ]   ; backlog
breed [ feedbacks feedback ]

customers-own [
  feature_wanted
  my_feedback
]

features-own [
  id
  fitness
]

stories-own [
  id
  feedback_count
]

feedbacks-own [
  id
]

to setup
  clear-all
  set max_initial_feature_set 3
  draw-market
  populate-market
  reset-ticks
  set has_gone_to_market? false
  go_to_market
end

to go
  ask customers [
    move
    make_business_contact
  ]
  ask feedbacks [
    move-feedback
    turn-into-story
  ]
  if ticks mod 1000 = 0 [ build_features ]
  tick
end

to go_to_market
  if has_gone_to_market? [stop]
  define-initial-features
  order-features
  order-backlog
  set has_gone_to_market? true
end

to draw-market

  ask patches [ set pcolor white ]

  ; market distance
  set customer_patches patches with [pxcor > -3]
  ask customer_patches [ set pcolor blue ]
  ask patches with [pxcor = (max-pxcor / 2) and pycor = min-pycor] [set plabel "customers"]

  ; company area
  set feature_patches patches with [pxcor < -3]
  ask feature_patches [ set pcolor green ]
  ask patches with [pxcor = (max-pxcor / -2) and pycor = min-pycor] [set plabel "company"]

  ; company external interface (channel)
  ask patches with [pxcor = -3]
    [ set pcolor black ]

end

to-report random-pareto [alpha mm]
  report mm / ( random-float 1 ^ (1 / alpha) )
end

to-report feature-distribution-value
  if (first feature_distribution = "1") [report 1.0]
  if (first feature_distribution = "2") [report .5]
  if (first feature_distribution = "3") [report .2]
end

to populate-market
  create-customers total_market_size [
    set color white
    set size .8
    ; set feature_wanted n-values 3 [random (max_initial_feature_set * feature_set_gap)]
    set feature_wanted n-values 3 [round random-pareto 1 feature-distribution-value]
    set my_feedback [feature_wanted] of self
    move-to-empty-one-of customer_patches
  ]
  set total_market_feature_set_ids remove-duplicates shuffle (reduce sentence ([feature_wanted] of customers))
end

to define-initial-features
  let max_initial_feature_set_length min (list max_initial_feature_set (length total_market_feature_set_ids))
  let initial_feature_set_ids n-values max_initial_feature_set_length [i -> item i total_market_feature_set_ids]

  foreach initial_feature_set_ids [fid ->
    create-features 1 [
      set-feature-details
      set id fid ]
  ]
end

to set-feature-details
  set color blue
  set xcor min-pxcor
  set ycor max-pycor
  set heading 0
  set shape "box"
end

to set-story-details
  set color gray
  set xcor min-pxcor
  set ycor max-pycor
  set heading 0
  set shape "book"
end

to build_features
  let max_stories min (list count stories 3)
  let first_stories sublist ordered-backlog 0 max_stories
  foreach first_stories [s ->
    transform-into-feature s]
  order-features
  order-backlog
end

to transform-into-feature [storie]
  let sid [id] of storie
  ask storie [die]

  if member? sid [id] of features [stop]

  create-features 1 [
    set id sid
    set-feature-details
  ]
end

to move  ; turtle procedure
  lt random-float 20
  rt random-float 20
  ifelse patch-ahead 1 = nobody
         or [pcolor] of patch-ahead 1 = black
      [ lt random-float 360 ]   ;; We see a wall in front of us. Turn a random amount.
      [ fd .1 ]                ;; Otherwise, it is safe to move forward.
end

to move-feedback
  fd .3
  let xlaststory item 0 story-to-follow
  let ylaststory item 1 story-to-follow
  facexy xlaststory ylaststory
end

to turn-into-story

  let xlaststory item 0 story-to-follow
  let ylaststory item 1 story-to-follow
  if not (round [xcor] of self = round xlaststory
    and round [ycor] of self = round ylaststory)
  [ stop ]

  let my_id [id] of self
  let known_story one-of stories with [id = my_id]

  ifelse (known_story = nobody)
  [
    hatch-stories 1 [
      set-story-details
      set id my_id ]
  ]
  [
    ask known_story [
      set feedback_count feedback_count + 1
      set color (feedback_count / 2) + gray
      set label feedback_count
    ]
  ]

  order-backlog
  die

end

to-report story-to-follow
  let xlaststory min-pxcor
  let ylaststory max-pycor
  if not (last_backlog_story = nobody or last_backlog_story = 0) [
    set xlaststory [xcor] of last_backlog_story
    set ylaststory [ycor] of last_backlog_story
  ]

  report (list xlaststory ylaststory)
end

to make_business_contact
  if patch-ahead 1 = nobody [stop]
  if [pcolor] of patch-ahead 1 != black [stop]

  if length [feature_wanted] of self = 3 [set shape "circle"]

  let will_give_feedback? false
  foreach sort features [f ->
    if member? ([id] of f) ([feature_wanted] of self) [
      ask f [set fitness fitness + 1]
      ask self [
        happier-customer [id] of f
      ]
      set will_give_feedback? true
      order-features
    ]
  ]

  ask self [if will_give_feedback? [give-feedback]]
end

to happier-customer [feature_id]
  let i_want_this [feature_wanted] of self
  set i_want_this remove feature_id i_want_this
  set feature_wanted i_want_this

  let i_told_this remove feature_id [my_feedback] of self
  set my_feedback i_told_this

  if length i_want_this = 2 [set shape "face sad"]
  if length i_want_this = 1 [set shape "face neutral"]
  if length i_want_this = 0 [set shape "face happy"]
end

to give-feedback
  if empty? [my_feedback] of self [stop]

  let my_fb one-of ([my_feedback] of self)
  let xlaststory item 0 story-to-follow
  let ylaststory item 1 story-to-follow
  hatch-feedbacks 1 [
    set id my_fb
    facexy xlaststory ylaststory
    set color pink
  ]
  set my_feedback remove my_fb [my_feedback] of self
end

to move-to-empty-one-of [locations]  ;; turtle procedure
  move-to one-of locations
  while [any? other turtles-here and (pcolor = black) ] [
    move-to one-of locations
  ]
end

to order-backlog
  let sorted_stories ordered-backlog
  if sorted_stories = [] [stop]
  let first_story first sorted_stories
  if first_story = nobody [stop]
  ask first_story [
    set xcor min-pxcor
    set ycor max-pycor
  ]
  foreach sorted_stories [s ->
    order-vertically first_story s
    set first_story s
    set last_backlog_story s
  ]

end

to-report ordered-backlog

  ifelse first backlog_prioritization = "2" [
    ; by-customer-feedback
    report sort-on [(- feedback_count)] stories
  ][
    ; random
    report shuffle sort stories
  ]
end

to order-features
  let sorted_features sort-on [(- fitness)] features
  if sorted_features = [] [stop]
  let first_feature first sorted_features
  ask first_feature [
    set xcor (min-pxcor) / 2
    set ycor max-pycor
  ]
  foreach sorted_features [f ->
    order-vertically first_feature f
    set first_feature f
    ask f [update-feature-status]
  ]
end

to order-vertically [previous next]
  if previous = nobody [stop]

  ifelse [ycor] of previous - 2 < min-pycor
    [ask next [
       set ycor max-pycor - 1
       set xcor [xcor] of previous + 1 ]]
    [ask next [
       set ycor [ycor] of previous - 1
       set xcor [xcor] of previous]
  ]
end

to update-feature-status
  set color (fitness / 3) + sky
  set label fitness
end
@#$#@#$#@
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BUTTON
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NIL
setup
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OBSERVER
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go
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OBSERVER
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PLOT
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customers
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NIL
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"" ""
PENS
"happy" 1.0 0 -8862290 true "" "plot count customers with [length feature_wanted = 0]"
"neutral" 1.0 0 -723837 true "" "plot count customers with [length feature_wanted = 1]"
"sad" 1.0 0 -1604481 true "" "plot count customers with [length feature_wanted = 2]"
"not customer" 1.0 0 -5298144 true "" "plot count customers with [length feature_wanted = 3]"
"total" 1.0 0 -16777216 true "" "plot total_market_size"

SLIDER
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total_market_size
total_market_size
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people or companies
HORIZONTAL

MONITOR
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features delivered
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1
11

MONITOR
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441
146
total addressable market
count customers
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MONITOR
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served available market (%)
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MONITOR
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features in use
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MONITOR
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"" ""
PENS
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"desired" 1.0 0 -16777216 true "" "plot length total_market_feature_set_ids"

MONITOR
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MONITOR
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PLOT
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feedback
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"" ""
PENS
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CHOOSER
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backlog_prioritization
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0

PLOT
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 assets
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"" ""
PENS
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"[active] feature value" 1.0 0 -7500403 true "" "plot sum [fitness] of features"

CHOOSER
490
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728
96
feature_distribution
feature_distribution
"1 - concentrated" "2 - highly concentrated" "3 - extremely concentrated"
0

@#$#@#$#@
## 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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@#$#@#$#@
NetLogo 6.0.2
@#$#@#$#@
@#$#@#$#@
@#$#@#$#@
<experiments>
  <experiment name="simulation" repetitions="5" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <exitCondition>((count customers with [length feature_wanted = 0]) / total_market_size) &gt; .5</exitCondition>
    <metric>ticks</metric>
    <metric>count customers with [length feature_wanted = 0]</metric>
    <metric>sum [feedback_count] of stories</metric>
    <metric>sum [fitness] of features</metric>
    <enumeratedValueSet variable="total_market_size">
      <value value="10"/>
      <value value="70"/>
      <value value="500"/>
      <value value="1000"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="backlog_prioritization">
      <value value="&quot;1 - by intuition (random)&quot;"/>
      <value value="&quot;2 - by customer feedback&quot;"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="feature_distribution">
      <value value="&quot;1 - concentrated&quot;"/>
      <value value="&quot;2 - highly concentrated&quot;"/>
      <value value="&quot;3 - extremely concentrated&quot;"/>
    </enumeratedValueSet>
  </experiment>
</experiments>
@#$#@#$#@
@#$#@#$#@
default
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@#$#@#$#@
0
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