Bayes Network Assignment
Dan Collins
1183446
COMP316-14A

This assignment builds a bayes network, and then infers probabilities
using rejection sampling, likelihood weighting and markov-chaining
monte carlo (MCMC).

The inferences are the same across the three methods, so the outputs
are close to the same value.

To run, simply use 'python BayesNet.py', and the interpreter will take
care of the rest.

Note that the last experiment for each inference takes a long time.
Python isn't the fastest.  Java was significantly faster (tested with
rejection sampling).