The following is an outline of general expectations:
- Keep up with soft deadlines set within the team. Treat it like the final deadline.
- It is important that the team at least tries to show up to meetings.
- Communicate if you are unable to complete something on time so you can get help on it.
- Being interested in the project is a great way to encourage efficiency and collaborative spirit. If there are any readings, do them.
- Do things that you are good at so we have a good deliverable. That does not mean that work is delegated unreasonably or disproportionately, however.
- We will be doing accountability checks, rather than full-scale meetings. The team agrees that longer meetings are counter-productive unless they are meant for discussion. Most communication can be done via messaging. This accountability check is scheduled weekly on Tuesdays at 3 pm.
- We will avoid working last minute.
- While meetings will not be enforced, one-on-one in-person or virtual meetings are encouraged between two or more people working on something large or potentially complicated.
- Design a model to valuate the risk of war, given a graph network of alliances and enmities, focusing on international conflicts.
- Venture out, if possible, to other predictive analytics relevant to the primary goal, like modeling war from economic growth, or the lack thereof. This is not our priority.
- Eventually delve into, if possible, civil conflicts and intranational unrest, as well as the effect of local economies as a lone predictor of conflict. This is not our priority.
- Back our findings and models with a strong mathematical background.
These will keep changing as we progress.
- Kyle Cowden - Mathematical Background, Initial Predictive Algorithm, and Evolution Algorithm.
- Lowell Monis - Predictive Machine Learning Methods, Mathematical Assistance, Data Collection
- Joseph Burke - Data Collection and Processing, Miscellaneous Machine Learning Techniques
- Saif Sheikh - Miscellaneous Machine Learning Techniques
Each member will be responsible for presenting their work