Dear Fabio;
concerning the issue of randomly generating Bayes Nets, it may be
of your interest to know that an optimally efficient solution to
the problem of uniformly sampling the set of distribution functions
for a discrete, n-valued random variable is published on the Los
Alamos e-print archive (http://eprints.lanl.gov) as MATH-0011025 (3
Nov. 2000). Also directly accessible at:
http://eprints.lanl.gov/cgi-bin/w3vdkhgw?qryAAA0n_xre;math-0011025
cheers.
alessandra potrich
>
> 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
>
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