CODEWITHSUNDEEP
netlogobehaviorspace
bugandbeetle
bugandbeetle

Reputation: 1

why are my results from behaviorspace (netlogo) so inconsistent?

I am somewhat new to Netlogo, and have been scratching my head over some of the results I get from behaviorspace. I have been playing with the wolf-sheep predation model, and changing their movement based on what color patch they are in. There is a single wolf and a single sheep, and what I want to measure is the number of time steps it takes for the wolf to eat the sheep. The patches are colored randomly, based on some proportion from 0-100, as below:

to color-patches
  let total 100
  let p-red   slider1 / total
  let p-green total - p-red


  ask patches [
    let x random-float 1.0
    if x <= p-red + p-green [set pcolor green]
    if x <= p-red [set pcolor red]
  ]
end

The issue I am having is when I set the movement of the wolf and the sheep to move independently of the patch color:

ask sheep [
    set heading random 360
    fd 1
  ]
  
  ask wolves[
    set heading random 360
    fd 1
    eat-sheep
  ]

My expectation is that the mean and standard error for the number of time steps until the wolf eats the sheep should be pretty similar regardless of how many red patches and how many green patches there are, since their movement is not affected by it. I ran it in behaviorspace, with 1000 iterations per 10% increase in proportion of red patches (from 0 - 100%). However, I keep getting results that look kind of like this:

enter image description here

Basically the means+se are all over the place. Every time I run it, they are distributed differently (but same grand mean). This is particularly odd since when I introduce any sort of patchcolor-specific behavior for either the wolf or the sheep, I get very clear patterns with less variation.

Any ideas what might be going on here? The only thing I could think of is that relative starting position of each is pretty important (but each is placed at random xy coords). I assumed that in behaviorspace for each iteration for a given set of parameters, it would run through all the code (thus generating a new random landscape and new random starting points for the wolf and the sheep for each of the 1000 runs per parameter combination). Does behaviorspace maybe take the first landscape and starting coordinates for each turtle and use them for each of the 1000 iterations per parameter combination?

Thanks!

Upvotes: 0

Views: 81

Answers (1)

Steve Railsback
Steve Railsback

Reputation: 1736

Now I think you may not have a mistake but instead are just misinterpreting your graph. The Y axis on the graph you posted ranges only from 2000 to 2200; if you set the Y axis scale to 0 to 2500, the results from each experiment would look very similar to each other.

The difference in mean between your results (~2100) and my results (~3100) is probably just due to different world sizes. I presented standard deviation while you graphed standard error.

If you histogram the results, they seem to follow an exponential distribution.

Upvotes: 1

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