1. This page
This page is a workspace for your group modeling project. Use it to conduct group discussions, to write collaborative code, to make tasks lists, to store information for your group to use.Create new pages linked from this page if you need to. Create lots of pages if necessary.
2. Next meeting
Wednesday, April 2, 10:30 pm at Park 232.3. Useful links
Bio/Geo/CS250 MainModelingWiki4. Useful tasks
The phenomenon-
(Describe here the real-world phenomenon you are trying to reproduce in your model. Be as specific or vague as you like, but make it clear how you will know whether or not your model does reproduce the phenomenon. Be specific: will you look to see if some variable is within some numerical range? Will you look for qualitative patterns -- and if so, what counts as matching those patterns?)
The actors and variables
-
(Describe here the structural constituents of your model. What are the entities that interact to produce the behavior? Spatial locations, agents, state variables, something else?)
The dynamic
-
(Describe here how the state of your model (the population sizes, the states of the CA cells, whatever) is transformed into the state of the model in the next time step. You might describe CA or L-system transition rules, equations describing changes over a time step, or agent behavior rules.)
The oversimple model
-
(Describe here the oversimplified skeleton of the model with which you'll start. This oversimple model will probably not produce the behavior you're looking for, but it'll help you test your code, it'll help you structure your exploration of the model, and it'll help you keep your thoughts organized.)
The test-and-modify cycle
-
(You'll try your oversimple model and compare its behavior to the phenomenon you're trying to reproduce. If it doesn't match, you'll change the model (maybe you'll add a component) and try again. Don't describe your plan here: this process is largely improvisational, and you shouldn't try to plan it out ahead of time.)
Exploration
-
(What variables turn out to be important? Do a sensitivity analysis. What implementation choices turn out to be important? Try representing some interaction with a differently shaped function and see if the results differ greatly. How general is the model? Try running the model with different plausible sets of variables.)
