Simple Social Dynamic

Simple Social Dynamic preview image

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Tags

grid 

Tagged by Arthur Dolgopolov 7 months ago

social dynamics 

Tagged by Arthur Dolgopolov 7 months ago

social norms 

Tagged by Arthur Dolgopolov 7 months ago

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WHAT IS IT?

This is a simple model of emergence of social norms played on a grid.

HOW IT WORKS

Every period each player is randomly matched with one of their four neighbors in a cross pattern (above,below,left,right) and both have to pick A or B.

The payoffs from their choices are determined according to the Stag Hunt game:

A B
A 10,10 0,x
B x,0 x,x

x is the value of the slider payoff_B.

The players maximize the expected payoff - the average payoff from playing the chosen action against every one of the four neighbors.

The game captures a similar intuition as the famous Prisoner dilemma: a conflict between safety and cooperation. In particular, notice that A is payoff-dominant (it Pareto-dominates the other action, i.e. both players are strictly better off), while B is risk-dominant.

The model closely follows Durlauf and Young (2004).

HOW TO USE IT

Click setup to randomly populate the grid with players that take one of the two actions. You can manually change the action of any player using the two buttons. Adjust the slider to change the value of the maxmin payoff x. Then click Run. The model will stop once it reaches a stable configuration.

THINGS TO TRY

Try to change the risk-dominant action by setting the slider above and below 5.

References

Durlauf, Steven N., and H. Peyton Young, eds. Social dynamics. Vol. 4. Mit Press, 2004.

Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.

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Click to Run Model

patches-own
[
  action ;; my action (0 or 1)
  total  ;; sum of actions of 4 neighbor
  stable ;; is stable?
]

to setup
  clear-all
  ask patches
    [ set action random 2
      recolor-patch ]
  reset-ticks
end 

to go
  let any-actions-changed? false

  ask patches [
    set total (sum [action] of neighbors4)
    if total * 10 > payoff_B * 4 and action = 1 [
      set stable 1
    ]
    if total * 10 < payoff_B * 4 and action = 0 [
      set stable 1
    ]
    if total * 10 > payoff_B * 4 and action = 0 [
      set stable 0
    ]
    if total * 10 < payoff_B * 4 and action = 1 [
      set stable 0
    ]
    if total * 10 = payoff_B * 4 [
      set stable 0
    ]
  ]

  ifelse not all? patches [stable = 1] [
    ask one-of patches with [stable = 0]
    [
      let previous-action action
      if total * 10 > payoff_B * 4;;total * 2 + ( 4 - total ) * 2
      [
        set action 1
      ]
      if total * 10 < payoff_B * 4 ;;total * 2 + ( 4 - total ) * 2
      [
        set action 0
      ]
      if total * 10 = payoff_B * 4;;total * 4 + ( 4 - total ) * 0 = 2 ;;total * 2 + ( 4 - total ) * 2
      [
        set action (random 2)
      ]
      if action != previous-action
        [ set any-actions-changed? true ]
      recolor-patch
    ]
  ]
  [
    if not any-actions-changed? [ stop]
  ]
  tick
end 

to recolor-patch  ;; patch procedure
  ifelse action = 0
    [ set pcolor [35 95 164] ]
  [ set pcolor [255 147 79] ]
end 

to set_action_one
  if mouse-down? [
    ask patch mouse-xcor mouse-ycor [
      set action 1
      recolor-patch
    ]
  ]
  display
end 

to set_action_zero
  if mouse-down? [
    ask patch mouse-xcor mouse-ycor [
      set action 0
      recolor-patch
    ]
  ]
  display
end 

There are 4 versions of this model.

Uploaded by When Description Download
Arthur Dolgopolov 7 months ago Table Download this version
Arthur Dolgopolov 7 months ago Table Download this version
Arthur Dolgopolov 7 months ago Description and variable names Download this version
Arthur Dolgopolov 7 months ago Initial upload Download this version

Attached files

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