Dear UAIers,
I would appreciate if anyone could give some pointers
on how to generate Bayesian networks randomly. That is,
how to construct directed acyclic graphs and their
associated parameters in a way that uniformly samples
the space of the DAGs? I have not found a simple explanation
on how to do it, even though many papers refer to networks
that have been generated randomly. I wonder if there is
software available for this.
Maybe the problem is simple, but it does seem to require
some sophistication. Even to generate the conditional
probabilities, it does not seem that simply generating
tuples and normalizing them will uniformly sample the
space of probability distributions.
Any help is appreciated. Thanks,
Fabio Cozman
