CS108L Lab 11: Independent
Rubric Example: Wolf-SheepPredation Model
In this example we will build upon the Wolf-Sheep-Predation model in the model
library. This is different than building a model from scratch because someone
(and that someone can be you) has already built a model. What we will be doing is
adding to the model to make it significantly different than the original. This
particular model is one of wolf eating sheep. We want to build upon that so we will
add things that affect the sheep survivability. What we decide to do is allow the
sheep a chance to see the wolves and flee, add a shepherd to protect the sheep
and finally a dog to chase the wolves away. These features will both have an
impact on the original model and make it significantly different.
Milestone 2: The Proposal (Worth 10 points)
The proposal is described in the document Independent Project Proposal you may
obtain from the class web page. It is not repeated here.
Milestone 3: The first week (Worth 10 points)
Unlike the ‘from scratch rubric’, we already have a foundation provided to us. So
we will simply start adding our features. The first one is the sheep fleeing. We
need to detect the wolves but we also don’t want to always detect the wolves so
wolves can sneak up on the sheep. We break down these ideas as follows:
Activity: Sheep fleeing
A. Add a sheeps-own variable called sight. Sight is the number of patch ahead
a sheep can see. Add a slider for this. [1pt]
B. Add a wolves-own variable called hide. Hide is the probability a wolf will not
be seen if a wolf is within a sheep’s sight. Add a slider for this as well. [1pt]
C. Make sheep flee wolves if they see a wolf within (note that this is up to and
including the sight) their sight. Sheep will run the opposite direction of the
first wolf INSTEAD of doing their typical wiggle walk. [4pts]
D. Let’s collect some data on various sight ranges and hide probabilities to find
a good balance or when it tips the scales one way or another. [4pts]
Milestone 4: The second week (Worth 10 points) due date 11/28/16
Our next feature is the shepherd. The shepherd doesn’t actively do anything he is
just scary to the wolves. We decide to represent this as an area the wolves will do
their best to avoid. If they do enter the area they will try and leave as soon as
they can.
Activity: Add shepherds
A. Create a breed called shepherds. Shepherds look like people. Shepherds
have their own variable called safety_radius. This determines the number
of patches around the shepherd that a wolf will not enter. Let’s give it a
slider so we can find a good setting. [3pts]
B. When a wolf starts to enter a shepherd’s safety_radius it instead moves in
a direction away from the shepherd. Note that a wolf will never move into a
shepherd’s radius so if there are more than one shepherd it will take the
open path or just sit there if no path is open. If a shepherd moves over the
wolf it will flee the area away from the shepherd. This movement is done
INSTEAD of normal movement. [5pts]
C. Collect some data for different numbers of shepherds and safety_radii.
For this keep the sight range and hide numbers at the good balance point
from milestone 1 above. [2pts]
Milestone 5: The final project (Worth 40 points) due date 12/9/16 by
11:59pm via the standard turn in system.
We are almost done. Part of this milestone’s rubric is written (the first 20 points).
For that portion refer to the Independent Project Proposal on the class website.
The remainder of the points (‘E’) from the Proposal document is up to us. To finish
off this model we need to add the dogs. Dogs chase wolves to protect the sheep
and wolves run from dogs. So we have a few different steps we need to take care
of and we want to collect data to see how our model performs.
Activity: We add our dogs
A. Create a new breed call dogs. Dogs have a variable called sight that says
how many patches ahead it can see a wolf. Add a slider for this. [2pts]
B. If a dog sees a wolf (within it sight) it will run after the wolf until it
cannot see it. [4pts]
C. If a dog is on the same patch as a wolf a wolf will flee. When fleeing the
wolf moves twice as far as a DOG’s movement for a number of ticks = to
the dog’s sight. This keeps the dogs from always catching up [8pts]
D. We will run some tests to find out a good balance for this feature, we
will make the previous features constant at their best value for this
test. [6pts]
And that completes are rubric. We need to take the completed proposal and go
over it with an instructor. In talking through these items we will likely find things
we want to change, add or remove depending on the instructor’s feedback.