Scenario: The environment has two unlimited sources (food and water), in a substantial distance from each other. The donkey has a general metabolism that continuously consumes food and water reserves in the body. If any of the two reserves drops to zero, the donkey dies.

(Simplifying) assumptions:

• Linear decrease in both water and food reserves in the body, higher under activity (e.g., traveling).
• No other needs or tasks (e.g., no predators, no sleep necessary).
• Eating, drinking, and traveling takes a substantial amount of time.
• The donkey has a representation of the environment and knows where the two sources are.

Task: Construct an organism, with as few assumptions as possible, that survives as long as possible. Which constructs / sensors / abilities are necessary for this? Assume as simple abilities as possible - certainly not super-human abilities. (Rather think of an amoeba, not a super-AI).

Deliverable: A markdown text file with a verbal description of the organism. Give it the version number 0.1.0. Upload to the Git repo.

Task:

1. List all parameters of your model (on the top of your markdown file).
   → As a heuristic: Every conrete number that you need for the formulas of your simulation is a parameter.
2. Categorize them into fixed and free parameters. → Virtually all parameters (except natural constants) could be imagined as being free. It is usually a choice to fix some of them in order to simplify the model.
3. List all input/predictor variables
4. List all primary ouput variables.

• In some models, an output variable can also be an input variable for something else.
• Do not list intermediate/temporary variables that are only necessary for computations.
• Do list mediating variables that are psychologically meaningful (e.g. an emotion that mediates the process between stimulus (= input) and action)

Cf. linear regression: \(\color{red} y = \color{forestgreen} \beta_0 \color{black} + \color{forestgreen} \beta_1 \color{blue} x\)
→ \(\color{red} y\) = output variable, \(\color{forestgreen} \beta\)s = parameters, \(\color{blue} x\) = input variable.

Task: Sketch your initial verbal model in the style of Bischof. Refine and extend where necessary, e.g.:

• Think about which sensors are necessary (both towards internal states and towards the environment) and which actors are necessary
• Give a label to every variable (i.e., every arrow in the graphical model).
• Every free parameter and input variable that you identified should be an arrow in your visual model

Deliverables:

• Draw the model collaboratively in draw.io. In one corner, add the updated version number and today’s date (simply as a text box).
• Create & switch to dev branch
• Export the graphical model as an xml file and push it to the Github repo. Increase version number in cff file.

Tasks:

• Define the variables in the implemented model:
  • Scale level
  • Possible range or discrete values (define the set)
  • Interpretability (what does a value of 0.7 mean?)
    • Maybe define operationalizations that give a meaning to the numbers
• Define computations for each box: How exactly are input variables transformed into the output variables? You need a concrete formula for that. Theories rarely are so specific that you can directly derive a formula; you probably need to fill many gaps with ad-hoc assumptions.
• Implement the model in Netlogo

Deliverables:

• Push the .nlogo file to your group’s Github repo.
• Update all written model descriptions, increase model version.
• Explain & justify the changes in the model in your CHANGELOG.md.
• Write a meaningful commit message.