The final project is a self-driven agent-based modeling analysis that culminates in a scientific paper.

The final paper and your model code will be **due the day of the final exam**.

- You may work alone or in pairs (three can work together but talk to me first since it can be hard to parse how much effort everyone put in)
- This project should be original work, but you are encouraged to tie in your own research or research interests—if this project can eventually lead to a paper or dissertation chapter that’s great! (Just be sure that it’s also something do-able in one semester!)
- I will periodically check in with you/your group throughout the semester to make sure you’re on track and that your project has a reasonable scope. There will be benchmarks included as part of some of the labs as well.

For the final paper, you will need to provide:

**The write-up**: I anticipate this will likely be 8-12 pages, but shorter or longer is fine so long as you fully cover the pieces described below**Your model**: I should be able to both review the code and run it myself if in NetLogo or Python. Your code must be*documented, clear, and readable*. Be sure to also document the version of python and versions of any packages you used.

**Paper Components**

*Introduction*. Provide an overview of the problem and a literature review. You should address: what gap or question are you addressing? What has been done before?*Methods**Model description*. Describe how your model works in terms of its: agents, interactions, environment, model schedule/timing- It’s a good idea to use the PARTE and ODD frameworks as a guide
- Flow charts & visuals are good! Illustrate the sequence of events in your model using a flow chart. Show how the agents operate, how and when interactions happen, the sequence of events in each time step, etc.
- From your model description, someone should be able to implement a version of your model

*Model analysis*. Describe the parameter settings you swept through and the analyses you ran. Someone should be able to recreate your analyses from your description, so be specific and complete!- If your model is stochastic, you may need to run multiple trials at the same parameter settings.

*Results*. Provide qualitative and quantitative summaries of how your model behaves. Provide graphs and plots of model outcomes at different settings as needed.*Discussion*. Return to the question or problem in your introduction—what do your results say about this problem? Put your results in a broader context. Describe the strengths, limitations, and potential future directions of your work.- If you think there are still some bugs driving your model’s behavior, this is the place to discuss this
- Also a good place to talk about how you might verify, validate, or extend the model in the future