# Homework

## Homework:

• In the mushroom hunt, were there always 80 red patches?
• Any questions about modified mushroom hunt model?
• Let’s talk about ODD exercise.

## Writing a model from an ODD

• Questions about writing a model from Butterfly ODD?
• Were there things the ODD was unclear about?

# Butterfly Model

## Enhancing the Butterfly model

patches-own
[
elevation
visited? ; question mark means it's a true/false variable
]

to setup
[
...
set visited? false
...
]
...
]

## Enhancing the Butterfly model

• Put a slider for q
• Add patches-own variable to indicate whether it was visited.
• Add turtles-own variable to remember the patch where it started.
• Increase the number of butterflies to 50.
• Stop butterfly from moving if it’s at the top of a hill.
• How can you tell whether it’s on the top?

## Enhancing the Butterfly model

• Write a reporter for corridor width

$\text{Corridor width} = \frac{\text{# patches visited}}{\text{distance from start}}$

• Put an observer on the interface
• Define a reporter:
to-report corridor-width
let wid ... ; calculate corridor width
report wid
end

# Behaviorspace

## Running Experiments: BehaviorSpace

• Vary any parameter that has a control on the model’s interface
• Writes output to .csv spreadsheet file (table output is the most useful).

## Output from BehaviorSpace Experiments

• Note: Data written in spreadsheet might be out of order.

"BehaviorSpace results (NetLogo 5.3.1)"
"jg_butterfly_1.nlogo"
"vary-q"
"01/25/2016 23:08:47:963 -0600"
"min-pxcor","max-pxcor","min-pycor","max-pycor"
"0","149","0","149"
"[run number]","q","[step]","corridor-width"
"4","0","999","424.71585264477375"
"3","0","999","407.8948972331853"
"2","0","999","402.16008464319225"
"1","0","999","413.09183879201066"
"5","0","999","380.4175502215263"
"6","0","999","408.25117143183326"
"7","0","999","431.37461560574894"
"8","0","999","408.38259535508286"
"9","0","999","421.7254402334981"

## Analyzing Behaviorspace Output

library(analyzeBehaviorspace)
launch_abs()

# Emergence

## Emergence

• A tricky concept.
• Growing Artificial Societies: “stable macroscopic patterns arising from the local interaction of agents.”
• Epstein ten years later: “I have always been uncomfortable with the vagueness and occasional mysticism surrounding this word.”
• Epstein now prefers to talk about “Generative Social Science”