This epic is to have a simulation that can demonstrate it can predict (and therefore reproduce) 80% of the data collected about the N2 worm in the WormBehavior database. This means building a training set and a test set that are kept separate from each other, using the training set to tune up the model, then generating predictions, and comparing them against the test set, and doing some cross-validation.

This epic focuses on an output of simulation performance rather than the means of implementation, so any way to achieve this epic is welcome.