Heroes and Cowards (exploration 13).nlogo

turtles-own [ friend enemy ]

to setup
  clear-all  
  ask patches [ set pcolor white ]  ;; create a blank background
  create-turtles number [
    setxy random-xcor random-ycor

    ;; set the turtle personalities based on chooser
    if (personalities = "brave")     [ set color blue ]
    if (personalities = "cowardly")  [ set color red ]
    if (personalities = "mixed")     [ set color one-of [ red blue ] ]
    
    ;; choose friend and enemy targets
    set friend one-of other turtles
    let turtles-not-including-friend [ other turtles ] of friend
    set enemy one-of other turtles-not-including-friend
  ]
  reset-ticks
end

to go
  ask turtles [
    if (color = blue)  [ act-bravely ]
    if (color = red)   [ act-cowardly ]
  ]
  tick
end

to act-bravely 
  ;; move toward the midpoint of your friend and enemy
  facexy ([xcor] of friend + [xcor] of enemy) / 2
         ([ycor] of friend + [ycor] of enemy) / 2
  fd 0.1
end

to act-cowardly 
  ;; put your friend between you and your enemy
  facexy [xcor] of friend + ([xcor] of friend - [xcor] of enemy) / 2
         [ycor] of friend + ([ycor] of friend - [ycor] of enemy) / 2
  fd 0.1
end

to preset-configuration [ seed ]
  ;; sets up the model for use with a particular random seed and constant
  ;; model parameters, so that a particular pattern can be re-created.
  set personalities "mixed"
  set number 68
  random-seed seed
  setup
end
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@#$#@#$#@
## ACKNOWLEDGEMENT

This model is from Chapter Two of the book "Introduction to Agent-Based Modeling: Modeling Natural, Social and Engineered Complex Systems with NetLogo", by Uri Wilensky & William Rand.

Wilensky, U & Rand, W. (2015). Introduction to Agent-Based Modeling: Modeling Natural, Social and Engineered Complex Systems with NetLogo. Cambridge, Ma. MIT Press.


## UPDATES TO THE MODEL SINCE TEXTBOOK PUBLICATION

In the textbook version of the code, there is a slight chance that a turtle's friend is also its enemy. Here, we prevent this from happening by choosing the enemy of a turtle amongst the set of other turtles not including its friend.

Also, we could not resist adding a few interesting preset configurations. Have fun playing with them!


## WHAT IS IT?

The "Heroes and Cowards" game, also called the "Friends and Enemies" game or the "Aggressors and Defenders" game dates back to the Fratelli Theater Group at the 1999 Embracing Complexity conference, or perhaps earlier.

In the human version of this game, each person arbitrarily chooses someone else in the room to be their perceived friend, and someone to be their perceived enemy.  They don't tell anyone who they have chosen, but they all move to position themselves either such that a) they are between their friend and their enemy (BRAVE/DEFENDING), or b) such that they are behind their friend relative to their enemy (COWARDLY/FLEEING).  

This simple model demonstrates an idealized form of this game played out by computational agents.  Mostly it demonstrates how rich, complex, and surprising behavior can emerge from simple rules and interactions.


## HOW IT WORKS

The rules of this model are that there are two basic personality types.  All agents in the model choose a friend and an enemy.  If they are in a COWARDLY mood, then the agent tries to keep their friend between them and their enemy.  If they are in a BRAVE mood, then the agent tries to stay between their enemy and their friend.


## HOW TO USE IT

Choose the NUMBER of turtles you want to examine, and choose whether the turtles should act COWARDLY, BRAVE, or MIXED.  Then press SETUP followed by GO to observe the patterns of behavior formed.

We also included some preset configurations. To try them out, just press the corresponding button, and then GO.


## THINGS TO NOTICE

Run the model many times and observe the different patterns of behavior.
INSPECT or WATCH some turtles so that you can see their individual behavior.


## EXTENDING THE MODEL

Modify the code to add more control over how many of each type of behavior there is.

Change the world wrapping rules to see how that effects the results.

You can create buttons that capture interesting patterns of behaviors by using the RANDOM-SEED function in NetLogo.  First set the RANDOM-SEED to different values. Press SETUP then GO and observe the behaviors. We created a `preset-configuration` procedure to makes it easy to create your own buttons that produce interesting behaviors. This procedure assumes a population of 68 turtles with "mixed" behaviors, but you could modify it to allow different settings.


## NETLOGO FEATURES

RANDOM-SEED initializes the NetLogo random number generator so that it always produces the same set of random numbers, enabling exact reproduction of model runs.


## CREDITS AND REFERENCES

This model is part of the textbook: Wilensky & Rand (2015). Introduction to Agent-Based Modeling: Modeling the Natural, Social and Engineered Complex Systems with NetLogo.

Versions of the Model are described in:

Bonabeau, E., & Meyer, C. (2001). Swarm intelligence. A whole new way to think about business. Harvard Business Review, 5, 107-114.

Bonabeau. E. (2012). http://www.icosystem.com/labsdemos/the-game/ .

Bonabeau, E., Funes, P. & Orme, B.  (2003). Exploratory Design Of Swarms. 2nd International Workshop on the Mathematics and Algorithms of Social Insects. Georgia Institute of technology, Atlanta, GA.

Sweeney, L. B., & Meadows, D. (2010). The systems thinking playbook: Exercises to stretch and build learning and systems thinking capabilities.
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