ConversationWorld

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Default-person Nathan Couch (Author)

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Model was written in NetLogo 6.0-M6 • Viewed 133 times • Downloaded 8 times • Run 0 times
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Click to Run Model

extensions [ls]

globals [
 meaning-language
 message-language
 objects
 relations

 all-meanings

 meaning-inputs
 message-inputs

 attempt-list
 accuracy-list
]

patches-own [ patch-meaning ]
turtles-own [ brain memory last-meaning last-message success?]

to setup

  clear-all
  ls:reset

  set attempt-list []
  set accuracy-list []

  ;; get the meaning and message languages set up
  generate-languages

  ;; give each patch a message
  ask patches [
    ;; there is a chance that the patch contains a relation, otherwise
    ;; there is an equal chance that it contains one or two objects
    ifelse (random 100) < relation-prob and num-relations != 0
      [ set patch-meaning generate-meaning 2 1 ]
      [ifelse num-objects > 1
        [ set patch-meaning generate-meaning (one-of (list 1 2)) 0 ]
        [ set patch-meaning generate-meaning 1 0 ]]

      ;; color the patch to weakly indicate what meaning it contains
      color-patch

      ]

  crt num-turtles [
    set color red
    setxy random-xcor random-ycor
    setup-brain
  ]

  reset-ticks
end 

to setup-test

  clear-all
  ls:reset

  set attempt-list []
  set accuracy-list []

  ;; get the meaning and message languages set up
  generate-languages

  ;; give each patch a message
  ask patches [

    ;; there is a chance that the patch contains a relation, otherwise
    ;; there is an equal chance that it contains one or two objects
    ifelse (random 100) > relation-prob and num-relations != 0
      [ set patch-meaning generate-meaning 2 1 ]
            [ifelse num-objects > 1
        [ set patch-meaning generate-meaning (one-of (list 1 2)) 0 ]
        [ set patch-meaning generate-meaning 1 0 ]
  ]]

  crt num-turtles [
    set color red
    setup-brain
    face patch-at min-pxcor min-pycor
  ]

  reset-ticks
end 

to go

  set attempt-list []


  ask turtles [
    move
    talk
    update
  ]

  ;; append to the end of the list the mean accuracy of the model at this tick
  set accuracy-list lput mean attempt-list accuracy-list
  tick
end 

;; TURTLE PROCEDURES

to setup-brain

 ;; sets up the turtle's brain

 set memory []
 (ls:load-headless-model "ConversationWorldBrain.nlogo" [ set brain ? ])
 ls:set-name brain (word "Brain of " self)
 (ls:ask brain [setup-brain ?1 ?2 ?3 ?4 ?5 ?6 ?7] meaning-language middle-layer num-middle-layers message-language meaning-to-message-iterations 10 learning-rate)
end 

to-report map-meaning [p-meaning]

  ls:let inputs1 map [member? ? p-meaning] meaning-language
  report ls:report brain [ apply-bools1 inputs1 ]
end 

to-report map-message [a-message]

  ls:let inputs2 map [member? ? a-message] message-language
  report ls:report brain [ apply-bools2 inputs2 ]
end 

to update

     ;; send the contents of memory to child model to improve the mapping
     (ls:ask [brain] of self [ update-mappings ?] memory )
end 

to move

  ;; turn and move a random amount
  rt (random 60) - 30
  forward 1
end 

to talk
  ;; pick someone to talk to
  let interlocutor one-of other turtles
  if (interlocutor != nobody) [

    ;; map the meaning to a message
    let message ( map-meaning [patch-meaning] of patch-here )

    ;; give the message to the other turtle and have them interpret it
    let recieved-meaning [map-message message] of interlocutor

    ;; check if there is a meaning mismatch
    ifelse recieved-meaning != map-meaning [patch-meaning] of patch-here
      [ set success? False ]
      [ set success? True  ]

    ;; encode the present interaction in memory
    set last-meaning map [member? ? [patch-meaning] of patch-here ] meaning-language
    set last-message [map-meaning map [member? ? [patch-meaning] of patch-here ] meaning-language ] of interlocutor
    set memory lput (list last-meaning last-message) memory

    ;; if the contents of memory exceed its capacity, forget the oldest thing in memory
    if length memory > memory-capacity
      [ set memory but-first memory]

    ;; recorde whether the interaction was succesful
    ifelse (success?) [set attempt-list lput 1 attempt-list ][set attempt-list lput 0 attempt-list ]
  ]
end 

;; PATCH PROCEDURES

to-report generate-meaning [ num-ob num-rel ]

  ;; helper function to generate messages
  let p-meaning ( list (n-of num-ob objects) (n-of num-rel relations))
  report flatten-list p-meaning
end 


;; GENERAL PROCEDURES

to generate-languages

  ;; sets up the language and meaning models
  generate-meaning-language
  generate-message-language
  set all-meanings generate-all-meanings
end 

to generate-meaning-language

  ;; generates the sets of objects and relations, then combines them into a single list.
  set relations map [ word "r" ? ] (n-values num-relations [?])
  set objects   map [ word "o" ? ] (n-values num-objects   [?])
  set meaning-language flatten-list (list objects relations)
end 

to generate-message-language

  ;; generates a list of words in the language
  set message-language map [ word "w" ? ] (n-values num-words [?])
end 

to-report generate-message

  ;; convience function to generate messages for the simple
  ;; brain used in the non-levelspace version of this model
  let word1 one-of message-language
  let word2 one-of message-language
  let word3 one-of message-language
  report (list word1 word2 word3)
end 

to-report generate-all-meanings

  ;; generates all possible meanings with the present language
  let two_meanings cartesian-product objects objects
  let three_meanings cartesian-product two_meanings relations
  report reduce sentence ( list objects two_meanings three_meanings )
end 

to-report cartesian-product [ list1 list2 ]

  ;; produces a list of all possible pairs where the first element of each pair
  ;; comes from the first list and the second element comes from the second list
  report reduce sentence map [ cartesian-helper ? list2 ] list1
end 

to-report cartesian-helper [ element list2 ]

  ;; required by cartesian-product to work well. This could also be used to generate
  ;; a version of cartesian-product that takes an arbitrary number of lists, but since
  ;; I only need it to work on two lists I'm sparing the effort.
  report map [ ( list element ?) ] list2
end 

to-report flatten-list [ lst ]
   ; flattens nested lists to a single list.
   if (reduce [?1 or is-list? ?2] fput false lst) [
     set lst reduce [sentence ?1 ?2] lst
     set lst flatten-list lst
   ]
   report lst
end 


;; Aesthetic functions

to color-patch

  ;; colors the patches so that the color and hue of the patch kiiinda indicates the meaning on it
  let vec map [member? ? patch-meaning ] meaning-language
  set vec map [ifelse-value ? [1][0]] vec
  set vec sum map [(5 * ? * (item ? vec)) + (50 * ?) ] n-values length vec [?]
  set pcolor vec
end 

;; REPORTERS

to-report windowed-accuracy [window-n]

  ;; indexes the last WINDOW members of accuracy-list and takes the mean
  ifelse window-n > length accuracy-list
    [ report 0 ]
    [ report mean map [item ? reverse accuracy-list] n-values window-n [?] ]
end 

to-report mean-attempt-list

  ifelse length attempt-list > 0
    [ report mean attempt-list ]
    [ report 0 ]
end 

There is only one version of this model, created almost 3 years ago by Nathan Couch.

Attached files

File Type Description Last updated
AMB-FinalPaper.docx word The Couch (2016) referred to in the documentation. almost 3 years ago, by Nathan Couch Download
ConversationWorldBrain.nlogo extension The code for the child models for this model. almost 3 years ago, by Nathan Couch Download

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